Articles | Volume 14, issue 11
https://doi.org/10.5194/gmd-14-6863-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Special issue:
https://doi.org/10.5194/gmd-14-6863-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Decadal climate predictions with the Canadian Earth System Model version 5 (CanESM5)
Reinel Sospedra-Alfonso
CORRESPONDING AUTHOR
Canadian Centre for Climate Modelling and Analysis, Environment and Climate Change Canada, University of Victoria, Victoria, BC, V8N 1V8, Canada
William J. Merryfield
Canadian Centre for Climate Modelling and Analysis, Environment and Climate Change Canada, University of Victoria, Victoria, BC, V8N 1V8, Canada
George J. Boer
Canadian Centre for Climate Modelling and Analysis, Environment and Climate Change Canada, University of Victoria, Victoria, BC, V8N 1V8, Canada
Viatsheslav V. Kharin
Canadian Centre for Climate Modelling and Analysis, Environment and Climate Change Canada, University of Victoria, Victoria, BC, V8N 1V8, Canada
Woo-Sung Lee
Canadian Centre for Climate Modelling and Analysis, Environment and Climate Change Canada, University of Victoria, Victoria, BC, V8N 1V8, Canada
Christian Seiler
Canadian Centre for Climate Modelling and Analysis, Environment and Climate Change Canada, University of Victoria, Victoria, BC, V8N 1V8, Canada
James R. Christian
Canadian Centre for Climate Modelling and Analysis, Environment and Climate Change Canada, University of Victoria, Victoria, BC, V8N 1V8, Canada
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- Decadal prediction of the probability of extreme seasons D. Befort & T. Kruschke 10.1088/1748-9326/adcc44
- Stratospheric Nudging And Predictable Surface Impacts (SNAPSI): a protocol for investigating the role of stratospheric polar vortex disturbances in subseasonal to seasonal forecasts P. Hitchcock et al. 10.5194/gmd-15-5073-2022
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- Verification Data and the Skill of Decadal Predictions G. Boer et al. 10.3389/fclim.2022.836817
- Improving long-term prediction of terrestrial water storage through integration with CMIP6 decadal prediction E. Zhu et al. 10.1016/j.atmosres.2024.107776
- Impact of climate changes in the suitable areas for Coffea arabica L. production in Mozambique: Agroforestry as an alternative management system to strengthen crop sustainability C. Cassamo et al. 10.1016/j.agee.2022.108341
- Ocean-atmosphere feedbacks key to NAO decadal predictability C. Patrizio et al. 10.1038/s41612-025-01027-7
- CAS FGOALS-f3-L Model Datasets for CMIP6 DCPP Experiment S. Hu et al. 10.1007/s00376-023-2122-x
- Skillful decadal prediction for Northwest Pacific tropical cyclone activity Y. Xu et al. 10.1007/s00382-024-07281-4
- Identifying a Pattern of Predictable Decadal North Pacific SST Variability in Historical Observations E. Gordon & N. Diffenbaugh 10.1029/2024GL112729
- Sugarcane water requirement and yield projections in major producing regions of China under future climate scenarios X. Zhu et al. 10.1007/s00704-023-04776-8
Latest update: 08 May 2025
Short summary
CanESM5 decadal predictions that started from observed climate states represent the observed evolution of upper-ocean temperatures, surface climate, and the carbon cycle better than ones not started from observed climate states for several years into the forecast. This is due both to better representations of climate internal variability and to corrections of the model response to external forcing including changes in GHG emissions and aerosols.
CanESM5 decadal predictions that started from observed climate states represent the observed...
Special issue