Articles | Volume 14, issue 2
https://doi.org/10.5194/esd-14-457-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/esd-14-457-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
21 Apr 2023
Research article |
| 21 Apr 2023
| 21 Apr 2023
Performance-based sub-selection of CMIP6 models for impact assessments in Europe
Tamzin E. Palmer
CORRESPONDING AUTHOR
Met Office Hadley Centre, FitzRoy Rd, Exeter, Devon, EX1 3PB, UK
Carol F. McSweeney
Met Office Hadley Centre, FitzRoy Rd, Exeter, Devon, EX1 3PB, UK
Ben B. B. Booth
Met Office Hadley Centre, FitzRoy Rd, Exeter, Devon, EX1 3PB, UK
Matthew D. K. Priestley
Department of Mathematics and Statistics, University of Exeter, Exeter, UK
Paolo Davini
Consiglio Nazionale delle Ricerche, Istituto di Scienze dell’Atmosfera e del Clima (CNR-ISAC), Turin, Italy
Lukas Brunner
Department of Meteorology and Geophysics, University of Vienna, Vienna, Austria
Leonard Borchert
Climate Statistics and Climate Extremes, Centre for Earth System Research and Sustainability (CEN), Universität Hamburg, Hamburg, Germany
Laboratoire de Météorologie Dynamique (LMD) at École Normale Supérieure (ENS), Paris, France
Matthew B. Menary
Met Office Hadley Centre, FitzRoy Rd, Exeter, Devon, EX1 3PB, UK
Laboratoire de Météorologie Dynamique (LMD) at École Normale Supérieure (ENS), Paris, France
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15 citations as recorded by crossref.
- Emergent Constrained Projections of Mean and Extreme Warming in China Z. Chen et al. 10.1029/2022GL102124
- Modeling Hydrological Responses of Watershed Under Climate Change Scenarios Using Machine Learning Techniques K. Karimizadeh & J. Yi 10.1007/s11269-023-03603-z
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- Climate model Selection by Independence, Performance, and Spread (ClimSIPS v1.0.1) for regional applications A. Merrifield et al. 10.5194/gmd-16-4715-2023
- Understanding the influence of “hot” models in climate impact studies: a hydrological perspective M. Rahimpour Asenjan et al. 10.5194/hess-27-4355-2023
- Developing climate services for vulnerable islands in the Southwest Indian Ocean: A combined statistical and dynamical CMIP6 downscaling approach for climate change assessment M. Leroux et al. 10.1016/j.cliser.2024.100491
- On the relation of CMIP6 GCMs errors at RCM driving boundary condition zones and inner region for Central Europe region E. Holtanová et al. 10.1007/s00382-024-07216-z
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- Emergent Constraints on Future Changes in Several Climate Variables and Extreme Indices from Global to Regional Scales H. Shiogama et al. 10.2151/sola.2024-017
- Environmental and energy analysis of the renovation of social housing buildings under various climate change scenarios and user profiles P. Hernandez-Cruz et al. 10.1016/j.jobe.2024.111164
- Forced trends and internal variability in climate change projections of extreme European windstorm frequency and severity M. Priestley et al. 10.1002/qj.4849
2 citations as recorded by crossref.
Latest update: 30 Dec 2024
Short summary
We carry out an assessment of an ensemble of general climate models (CMIP6) based on the ability of the models to represent the key physical processes that are important for representing European climate. Filtering the models with the assessment leads to more models with less global warming being removed, and this shifts the lower part of the projected temperature range towards greater warming. This is in contrast to the affect of weighting the ensemble using global temperature trends.
We carry out an assessment of an ensemble of general climate models (CMIP6) based on the ability...
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