Widespread changes in surface temperature persistence under climate change

Li, Jingyuan and Thompson, David W. J. ORCID: https://orcid.org/0000-0002-5413-4376 (2021) Widespread changes in surface temperature persistence under climate change. Nature, 599 (7885). pp. 425-430. ISSN 0028-0836

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Abstract

Climate change has been and will be accompanied by widespread changes in surface temperature. It is clear that these changes include global-wide increases in mean surface temperature and changes in temperature variance that are more regionally-dependent1–3. It is less clear whether they also include changes in the persistence of surface temperature. This is important as the effects of weather events on ecosystems and society depend critically on the length of the event. Here we provide an extensive survey of the response of surface temperature persistence to climate change over the twenty-first century from the output of 150 simulations run on four different Earth system models, and from simulations run on simplified models with varying representations of radiative processes and large-scale dynamics. Together, the results indicate that climate change simulations are marked by widespread changes in surface temperature persistence that are generally most robust over ocean areas and arise due to a seemingly broad range of physical processes. The findings point to both the robustness of widespread changes in persistence under climate change, and the critical need to better understand, simulate and constrain such changes.

Item Type: Article
Additional Information: Funding Information: Acknowledgements We thank A. Philips at NCAR for assistance with the Climate Variability Diagnostics Package analyses of the MMLEA; M. Winton and K. Rodgers for discussion of the GFDL ESM2M output; Z. Tan for providing output from the gray radiation and RRTMG simulations, and comments on the text; G. Drotos for providing the output from the RCE simulations and comments on the text; and F. Lehner, A. Czaja and B. Medeiros for helpful discussions. The large-ensemble output was obtained from the MMLEA produced by the US CLIVAR Working Group on Large Ensembles. We also acknowledge high-performance computing support from Cheyenne (https://doi.org/10.5065/D6RX99HX) provided by NCAR’s Computational and Information Systems Laboratory, sponsored by the National Science Foundation (NSF). All maps were made using the Proplot Matplotlib wrapper and map projections from the Cartopy Python package. J.L. and D.W.J.T. are supported by the NSF Climate and Large-Scale Dynamics program. Publisher Copyright: © 2021, The Author(s), under exclusive licence to Springer Nature Limited.
Uncontrolled Keywords: general,sdg 13 - climate action ,/dk/atira/pure/subjectarea/asjc/1000
Faculty \ School: Faculty of Science > School of Environmental Sciences
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Depositing User: LivePure Connector
Date Deposited: 15 Jul 2022 11:30
Last Modified: 12 Aug 2022 02:43
URI: https://ueaeprints.uea.ac.uk/id/eprint/86177
DOI: 10.1038/s41586-021-03943-z

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