Articles | Volume 7, issue 1
https://doi.org/10.5194/esd-7-71-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/esd-7-71-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
A novel bias correction methodology for climate impact simulations
Max Planck Institute for Biogeochemistry, Hans-Knöll-Str. 10,
07745 Jena, Germany
Institute for Atmospheric and Climate Science,
ETH Zürich, Rämistr. 101, 8075 Zürich, Switzerland
F. E. L. Otto
Environmental Change Institute, University of Oxford, South Parks
Road, Oxford OX1 3QY, UK
M. Forkel
Max Planck Institute for Biogeochemistry, Hans-Knöll-Str. 10,
07745 Jena, Germany
M. R. Allen
Environmental Change Institute, University of Oxford, South Parks
Road, Oxford OX1 3QY, UK
B. P. Guillod
Environmental Change Institute, University of Oxford, South Parks
Road, Oxford OX1 3QY, UK
M. Heimann
Max Planck Institute for Biogeochemistry, Hans-Knöll-Str. 10,
07745 Jena, Germany
M. Reichstein
Max Planck Institute for Biogeochemistry, Hans-Knöll-Str. 10,
07745 Jena, Germany
S. I. Seneviratne
Institute for Atmospheric and Climate Science,
ETH Zürich, Rämistr. 101, 8075 Zürich, Switzerland
K. Thonicke
Potsdam Institute for Climate Impact
Research, Telegrafenberg, 14473 Potsdam, Germany
M. D. Mahecha
Max Planck Institute for Biogeochemistry, Hans-Knöll-Str. 10,
07745 Jena, Germany
German Centre for
Integrative Biodiversity Research (iDiv), Halle-Jena-Leipzig, Deutscher Platz 5E, 04103 Leipzig, Germany
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65 citations as recorded by crossref.
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- The Impact of Meteorological and Hydrological Memory on Compound Peak Flows in the Rhine River Basin S. Khanal et al. 10.3390/atmos10040171
- From Hazard to Risk J. Sillmann et al. 10.1175/BAMS-D-17-0327.1
- Validation of a Rapid Attribution of the May/June 2016 Flood-Inducing Precipitation in France to Climate Change S. Philip et al. 10.1175/JHM-D-18-0074.1
- Climate Change Projections of Extreme Temperatures for the Iberian Peninsula C. Viceto et al. 10.3390/atmos10050229
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- Statistically bias-corrected and downscaled climate models underestimate the adverse effects of extreme heat on U.S. maize yields D. Lafferty et al. 10.1038/s43247-021-00266-9
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- Extreme heat in New Zealand: a synthesis L. Harrington & D. Frame 10.1007/s10584-022-03427-7
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- Influence mechanism of climate change over crop growth and water demands for wheat-rice system of Punjab, Pakistan M. Ahmad et al. 10.2166/wcc.2020.009
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- Attribution of Extreme Events to Climate Change F. Otto 10.1146/annurev-environ-112621-083538
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- A vast increase in heat exposure in the 21st century is driven by global warming and urban population growth T. Klein & W. Anderegg 10.1016/j.scs.2021.103098
- Changing population dynamics and uneven temperature emergence combine to exacerbate regional exposure to heat extremes under 1.5 °C and 2 °C of warming L. Harrington & F. Otto 10.1088/1748-9326/aaaa99
- Adapting attribution science to the climate extremes of tomorrow L. Harrington & F. Otto 10.1088/1748-9326/aaf4cc
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Saved (preprint)
Latest update: 10 Oct 2024
Short summary
We introduce a novel technique to bias correct climate model output for impact simulations that preserves its physical consistency and multivariate structure. The methodology considerably improves the representation of extremes in climatic variables relative to conventional bias correction strategies. Illustrative simulations of biosphere–atmosphere carbon and water fluxes with a biosphere model (LPJmL) show that the novel technique can be usefully applied to drive climate impact models.
We introduce a novel technique to bias correct climate model output for impact simulations that...
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