Journal article
Assessing observational constraints on future European climate in an out-of-sample framework
- Abstract:
- Observations are increasingly used to constrain multi-model projections for future climate assessments. This study assesses the performance of five constraining methods, which have previously been applied to attempt to improve regional climate projections from CMIP5-era models. We employ an out-of-sample testing approach to assess the efficacy of these constraining methods when applied to “pseudo-observational” datasets to constrain future changes in the European climate. These pseudo-observations are taken from CMIP6 simulations, for which future changes were withheld and used for verification. The constrained projections are more accurate and broadly more reliable for regional temperature projections compared to the unconstrained projections, especially in the summer season, which was not clear prior to this study. However, the constraining methods do not improve regional precipitation projections. We also analysed the performance of multi-method projections by combining the constrained projections, which are found to be competitive with the best-performing individual methods and demonstrate improvements in reliability for some temperature projections. The performance of the multi-method projection highlights the potential of combining constraints for the development of constraining methods.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
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(Preview, Version of record, pdf, 2.3MB, Terms of use)
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- Publisher copy:
- 10.1038/s41612-024-00648-8
Authors
- Publisher:
- Springer Nature
- Journal:
- npj Climate and Atmospheric Science More from this journal
- Volume:
- 7
- Issue:
- 1
- Article number:
- 95
- Publication date:
- 2024-04-26
- Acceptance date:
- 2024-04-15
- DOI:
- EISSN:
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2397-3722
- Language:
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English
- Keywords:
- Pubs id:
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1993536
- Local pid:
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pubs:1993536
- Deposit date:
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2024-04-30
Terms of use
- Copyright holder:
- O’Reilly et al.
- Copyright date:
- 2024
- Rights statement:
- Copyright © 2024, The Author(s). This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
- Licence:
- CC Attribution (CC BY)
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