Articles | Volume 15, issue 1
https://doi.org/10.5194/gmd-15-269-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-15-269-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Model evaluation paper
| Highlight paper
| 
13 Jan 2022
Model evaluation paper | Highlight paper |
| 13 Jan 2022
| 13 Jan 2022
Impact of increased resolution on long-standing biases in HighResMIP-PRIMAVERA climate models
Eduardo Moreno-Chamarro
CORRESPONDING AUTHOR
Barcelona Supercomputing Center (BSC), 08034, Barcelona, Spain
Louis-Philippe Caron
Barcelona Supercomputing Center (BSC), 08034, Barcelona, Spain
now at: Ouranos, Montréal, H3A 1B9, Canada
Saskia Loosveldt Tomas
Barcelona Supercomputing Center (BSC), 08034, Barcelona, Spain
Javier Vegas-Regidor
Barcelona Supercomputing Center (BSC), 08034, Barcelona, Spain
Oliver Gutjahr
Max Planck Institute for Meteorology, 20146 Hamburg, Germany
now at: Institut für Meereskunde, Universität Hamburg, 20146 Hamburg, Germany
Marie-Pierre Moine
CECI, Université de Toulouse, CERFACS/CNRS, 31100, Toulouse, France
Dian Putrasahan
Max Planck Institute for Meteorology, 20146 Hamburg, Germany
Christopher D. Roberts
ECMWF European Centre for Medium-Range Weather Forecasts, Reading, RG2 9AX, United Kingdom
Malcolm J. Roberts
Met Office, Exeter, CE2 EX1 3PB, United Kingdom
Retish Senan
ECMWF European Centre for Medium-Range Weather Forecasts, Reading, RG2 9AX, United Kingdom
Laurent Terray
CECI, Université de Toulouse, CERFACS/CNRS, 31100, Toulouse, France
Etienne Tourigny
Barcelona Supercomputing Center (BSC), 08034, Barcelona, Spain
Pier Luigi Vidale
NCAS-Climate, Department of Meteorology, University of Reading, Reading, RG6 6BB, United Kingdom
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32 citations as recorded by crossref.
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- Rectifying low-frequency variability in future climate sea surface temperature simulations: are corrections for extreme change scenarios realistic? C. Kusumastuti et al. 10.1088/1748-9326/accdf1
- Evidence for Atlantic Ocean forcing the atmosphere and the negative role of model bias R. Haarsma & S. Drijfhout 10.1038/s43247-025-02123-5
- The Northern Hemisphere Wintertime Storm Track Simulated in the High‐Resolution Community Earth System Model Z. Wang et al. 10.1029/2023MS003652
- Large-scale dynamics moderate impact-relevant changes to organised convective storms S. Chan et al. 10.1038/s43247-022-00669-2
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- Discrepancies in Simulated Ocean Net Surface Heat Fluxes over the North Atlantic C. Liu et al. 10.1007/s00376-022-1360-7
- Impact of increased resolution on the representation of the Canary upwelling system in climate models A. Sylla et al. 10.5194/gmd-15-8245-2022
- Bias correction of CMIP6 simulations of precipitation over Indian monsoon core region using deep learning algorithms T. Kesavavarthini et al. 10.1002/joc.8056
- Using high resolution climate models to explore future changes in post-tropical cyclone precipitation E. Bower & K. Reed 10.1088/1748-9326/ad2163
- Revisiting model complexity: Space-time correction of high dimensional variable sets in climate model simulations C. Kusumastuti et al. 10.1016/j.hydroa.2024.100193
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- Global Projections of Storm Surges Using High‐Resolution CMIP6 Climate Models S. Muis et al. 10.1029/2023EF003479
- Consistent responses to black carbon and carbon dioxide at global and 100 m model resolutions C. Stjern et al. 10.1038/s43247-025-02491-y
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Latest update: 15 Jul 2025
Short summary
Climate models do not fully reproduce observations: they show differences (biases) in regional temperature, precipitation, or cloud cover. Reducing model biases is important to increase our confidence in their ability to reproduce present and future climate changes. Model realism is set by its resolution: the finer it is, the more physical processes and interactions it can resolve. We here show that increasing resolution of up to ~ 25 km can help reduce model biases but not remove them entirely.
Climate models do not fully reproduce observations: they show differences (biases) in regional...
