Articles | Volume 16, issue 5
https://doi.org/10.5194/esd-16-1723-2025
© Author(s) 2025. 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-16-1723-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
15 Oct 2025
Research article |
| 15 Oct 2025
| 15 Oct 2025
Seamless seasonal to multi-annual predictions of temperature and Standardized Precipitation Index by constraining transient climate model simulations
Juan C. Acosta Navarro
CORRESPONDING AUTHOR
European Commission, Joint Research Centre, Ispra, Italy
Alvise Aranyossy
Barcelona Supercomputing Center (BSC), Barcelona, Spain
Paolo De Luca
Barcelona Supercomputing Center (BSC), Barcelona, Spain
Markus G. Donat
Barcelona Supercomputing Center (BSC), Barcelona, Spain
Institució Catalana de Recerca i Estudis Avançats (ICREA), Barcelona, Spain
Arthur Hrast Essenfelder
European Commission, Joint Research Centre, Ispra, Italy
Rashed Mahmood
National Center for Climate Research (NCKF), Danish Meteorological Institute, Copenhagen, Denmark
Andrea Toreti
European Commission, Joint Research Centre, Ispra, Italy
Danila Volpi
European Commission, Joint Research Centre, Ispra, Italy
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Near-term climate change projections are strongly affected by the uncertainty from internal climate variability. Here we present a novel approach to reduce such uncertainty by constraining decadal-scale variability in the projections using observations. The constrained ensembles show significant added value over the unconstrained ensemble in predicting global climate 2 decades ahead. We also show the applicability of regional constraints for attributing predictability to certain ocean regions.
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Short summary
A computationally inexpensive climate model analog method yields skillful climate predictions across timescales, from seasons to multiple years, complementing existing climate prediction systems and potentially providing valuable information for sectors like agriculture and energy.
A computationally inexpensive climate model analog method yields skillful climate predictions...
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