Articles | Volume 25, issue 1
https://doi.org/10.5194/hess-25-273-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-25-273-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Identifying robust bias adjustment methods for European extreme precipitation in a multi-model pseudo-reality setting
Danish Meteorological Institute, Copenhagen, Denmark
Peter Thejll
Danish Meteorological Institute, Copenhagen, Denmark
Peter Berg
Hydrology Research Unit, Swedish Meteorological and Hydrological Institute, Norrköping, Sweden
Fredrik Boberg
Danish Meteorological Institute, Copenhagen, Denmark
Ole Bøssing Christensen
Danish Meteorological Institute, Copenhagen, Denmark
Bo Christiansen
Danish Meteorological Institute, Copenhagen, Denmark
Jens Hesselbjerg Christensen
Danish Meteorological Institute, Copenhagen, Denmark
Physics of Ice, Climate and Earth, Niels Bohr Institute, University of Copenhagen, Copenhagen, Denmark
NORCE Norwegian Research Centre, Bjerknes Centre for Climate Research, Bergen, Norway
Marianne Sloth Madsen
Danish Meteorological Institute, Copenhagen, Denmark
Christian Steger
Deutscher Wetterdienst, Offenbach, Germany
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Cited
10 citations as recorded by crossref.
- Bias‐Adjustment Methods for Future Subdaily Precipitation Extremes Consistent Across Durations H. Van de Vyver et al. 10.1029/2022EA002798
- GEV Analysis of Extreme Rainfall: Comparing Different Time Intervals to Analyse Model Response in Terms of Return Levels in the Study Area of Central Italy M. Gentilucci et al. 10.3390/su151511656
- Comparison of statistical downscaling methods for climate change impact analysis on precipitation-driven drought H. Tabari et al. 10.5194/hess-25-3493-2021
- Uncovering the strengths and weaknesses of an ensemble of quantile mapping methods for downscaling precipitation change in Southern Africa S. Mendoza Paz & P. Willems 10.1016/j.ejrh.2022.101104
- Attributing heavy rainfall event in Berchtesgadener Land to recent climate change – Further rainfall intensification projected for the future B. Poschlod 10.1016/j.wace.2022.100492
- Applying a time-varying GEV distribution to correct bias in rainfall quantiles derived from regional climate models M. Onderka et al. 10.2478/johh-2024-0025
- On the need of bias adjustment for more plausible climate change projections of extreme heat M. Iturbide et al. 10.1002/asl.1072
- Improving the usability of climate services for the water sector: The AQUACLEW experience R. Pimentel et al. 10.1016/j.cliser.2022.100329
- An evaluation framework for downscaling and bias correction in climate change impact studies E. Vogel et al. 10.1016/j.jhydrol.2023.129693
- MIdASv0.2.1 – MultI-scale bias AdjuStment P. Berg et al. 10.5194/gmd-15-6165-2022
10 citations as recorded by crossref.
- Bias‐Adjustment Methods for Future Subdaily Precipitation Extremes Consistent Across Durations H. Van de Vyver et al. 10.1029/2022EA002798
- GEV Analysis of Extreme Rainfall: Comparing Different Time Intervals to Analyse Model Response in Terms of Return Levels in the Study Area of Central Italy M. Gentilucci et al. 10.3390/su151511656
- Comparison of statistical downscaling methods for climate change impact analysis on precipitation-driven drought H. Tabari et al. 10.5194/hess-25-3493-2021
- Uncovering the strengths and weaknesses of an ensemble of quantile mapping methods for downscaling precipitation change in Southern Africa S. Mendoza Paz & P. Willems 10.1016/j.ejrh.2022.101104
- Attributing heavy rainfall event in Berchtesgadener Land to recent climate change – Further rainfall intensification projected for the future B. Poschlod 10.1016/j.wace.2022.100492
- Applying a time-varying GEV distribution to correct bias in rainfall quantiles derived from regional climate models M. Onderka et al. 10.2478/johh-2024-0025
- On the need of bias adjustment for more plausible climate change projections of extreme heat M. Iturbide et al. 10.1002/asl.1072
- Improving the usability of climate services for the water sector: The AQUACLEW experience R. Pimentel et al. 10.1016/j.cliser.2022.100329
- An evaluation framework for downscaling and bias correction in climate change impact studies E. Vogel et al. 10.1016/j.jhydrol.2023.129693
- MIdASv0.2.1 – MultI-scale bias AdjuStment P. Berg et al. 10.5194/gmd-15-6165-2022
Latest update: 01 Apr 2025
Short summary
European extreme precipitation is expected to change in the future; this is based on climate model projections. But, since climate models have errors, projections are uncertain. We study this uncertainty in the projections by comparing results from an ensemble of 19 climate models. Results can be used to give improved estimates of future extreme precipitation for Europe.
European extreme precipitation is expected to change in the future; this is based on climate...
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