Articles | Volume 12, issue 4
https://doi.org/10.5194/esd-12-1543-2021
© 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/esd-12-1543-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Balanced estimate and uncertainty assessment of European climate change using the large EURO-CORDEX regional climate model ensemble
INRAE, UR ETGR, Univ. Grenoble Alpes, Grenoble, France
Samuel Somot
CNRM, Université de Toulouse, Météo-France, CNRS, Toulouse, France, 42 avenue Coriolis, 31057 Toulouse, France
Benoit Hingray
CNRS, IRD, Grenoble INP, IGE, Univ. Grenoble Alpes, Grenoble, France
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- Multi-Model Ensemble Machine Learning Approaches to Project Climatic Scenarios in a River Basin in the Pyrenees N. Bilbao-Barrenetxea et al. 10.1007/s41748-024-00408-x
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- Temperature characteristics over the Carpathian Basin‐projected changes of climate indices at regional and local scale based on bias‐adjusted CORDEX simulations C. Simon et al. 10.1002/joc.8045
- Regional climate model emulator based on deep learning: concept and first evaluation of a novel hybrid downscaling approach A. Doury et al. 10.1007/s00382-022-06343-9
Latest update: 20 Nov 2024
Short summary
This research paper proposes an assessment of mean climate change responses and related uncertainties over Europe for mean seasonal temperature and total seasonal precipitation. An advanced statistical approach is applied to a large ensemble of 87 high-resolution EURO-CORDEX projections. For the first time, we provide a comprehensive estimation of the relative contribution of GCMs and RCMs, RCP scenarios, and internal variability to the total variance of a very large ensemble.
This research paper proposes an assessment of mean climate change responses and related...
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