Articles | Volume 13, issue 4
https://doi.org/10.5194/esd-13-1437-2022
© 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/esd-13-1437-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Constraining low-frequency variability in climate projections to predict climate on decadal to multi-decadal timescales – a poor man's initialized prediction system
Barcelona Supercomputing Center, Barcelona, Spain
Department of Geography, University of Montreal, Montreal, Canada
Markus G. Donat
Barcelona Supercomputing Center, Barcelona, Spain
Institució Catalana de Recerca i Estudis Avançats (ICREA),
Barcelona, Spain
Pablo Ortega
Barcelona Supercomputing Center, Barcelona, Spain
Francisco J. Doblas-Reyes
Barcelona Supercomputing Center, Barcelona, Spain
Institució Catalana de Recerca i Estudis Avançats (ICREA),
Barcelona, Spain
Carlos Delgado-Torres
Barcelona Supercomputing Center, Barcelona, Spain
Margarida Samsó
Barcelona Supercomputing Center, Barcelona, Spain
Pierre-Antoine Bretonnière
Barcelona Supercomputing Center, Barcelona, Spain
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Cited
8 citations as recorded by crossref.
- Constraining decadal variability regionally improves near-term projections of hot, cold and dry extremes P. De Luca et al. 10.1088/1748-9326/acf389
- Optimizing Seasonal‐To‐Decadal Analog Forecasts With a Learned Spatially‐Weighted Mask J. Rader & E. Barnes 10.1029/2023GL104983
- How Credibly Do CMIP6 Simulations Capture Historical Mean and Extreme Precipitation Changes? M. Donat et al. 10.1029/2022GL102466
- Multi-decadal variation of ENSO forecast skill since the late 1800s J. Lou et al. 10.1038/s41612-023-00417-z
- New Potential to Reduce Uncertainty in Regional Climate Projections by Combining Physical and Socio‐Economic Constraints F. Lehner et al. 10.1029/2023AV000887
- Improving the forecast quality of near-term climate projections by constraining internal variability based on decadal predictions and observations M. Donat et al. 10.1088/2752-5295/ad5463
- Artificial intelligence for climate prediction of extremes: State of the art, challenges, and future perspectives S. Materia et al. 10.1002/wcc.914
- Twelve months at 1.5 °C signals earlier than expected breach of Paris Agreement threshold A. Cannon 10.1038/s41558-025-02247-8
8 citations as recorded by crossref.
- Constraining decadal variability regionally improves near-term projections of hot, cold and dry extremes P. De Luca et al. 10.1088/1748-9326/acf389
- Optimizing Seasonal‐To‐Decadal Analog Forecasts With a Learned Spatially‐Weighted Mask J. Rader & E. Barnes 10.1029/2023GL104983
- How Credibly Do CMIP6 Simulations Capture Historical Mean and Extreme Precipitation Changes? M. Donat et al. 10.1029/2022GL102466
- Multi-decadal variation of ENSO forecast skill since the late 1800s J. Lou et al. 10.1038/s41612-023-00417-z
- New Potential to Reduce Uncertainty in Regional Climate Projections by Combining Physical and Socio‐Economic Constraints F. Lehner et al. 10.1029/2023AV000887
- Improving the forecast quality of near-term climate projections by constraining internal variability based on decadal predictions and observations M. Donat et al. 10.1088/2752-5295/ad5463
- Artificial intelligence for climate prediction of extremes: State of the art, challenges, and future perspectives S. Materia et al. 10.1002/wcc.914
- Twelve months at 1.5 °C signals earlier than expected breach of Paris Agreement threshold A. Cannon 10.1038/s41558-025-02247-8
Latest update: 28 Mar 2025
Short summary
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.
Near-term climate change projections are strongly affected by the uncertainty from internal...
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