Articles | Volume 17, issue 22
https://doi.org/10.5194/gmd-17-8173-2024
https://doi.org/10.5194/gmd-17-8173-2024
Development and technical paper
 | 
19 Nov 2024
Development and technical paper |  | 19 Nov 2024

Robust handling of extremes in quantile mapping – “Murder your darlings”

Peter Berg, Thomas Bosshard, Denica Bozhinova, Lars Bärring, Joakim Löw, Carolina Nilsson, Gustav Strandberg, Johan Södling, Johan Thuresson, Renate Wilcke, and Wei Yang

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Cited articles

Andersson, S., Bärring, L., Landelius, T., Samuelsson, P., and Schimanke, S.: SMHI Gridded Climatology, Tech. rep., Swedish Meteorological and Hydrological Institute (SMHI), ISSN 0347-2116, 2021. a
Bellprat, O., Kotlarski, S., Lüthi, D., and Schär, C.: Physical constraints for temperature biases in climate models, Geophys. Res. Lett., 40, 4042–4047, https://doi.org/10.1002/grl.50737, 2013. a
Berg, P. and Södling, J.: MIdAS bias adjustment of extremes using Theil-Sen extrapolation: Data and plotting scripts for GMD-publication, Tech. rep., Zenodo [code and data set], https://doi.org/10.5281/zenodo.12570891, 2024. a
Berg, P., Bosshard, T., Yang, W., and Zimmermann, K.: MIdASv0.2.1 – MultI-scale bias AdjuStment, Geosci. Model Dev., 15, 6165–6180, https://doi.org/10.5194/gmd-15-6165-2022, 2022. a, b, c, d, e, f
Boé, J., Terray, L., Habets, F., and Martin, E.: Statistical and dynamical downscaling of the Seine basin climate for hydro‐meteorological studies, Int. J. Climatol., 27, 1643–1655, https://doi.org/10.1002/joc.1602, 2007. a
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Short summary
When bias adjusting climate model data using quantile mapping, one needs to prescribe what to do at the tails of the distribution, where a larger data range is likely encountered outside of the calibration period. The end result is highly dependent on the method used. We show that, to avoid discontinuities in the time series, one needs to exclude data in the calibration range to also activate the extrapolation functionality in that time period.
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