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Change in the magnitude and mechanisms of global temperature variability with warming

Brown, Patrick T. and Ming, Yi and Li, Wenhong and Hill, Spencer A. (2017) Change in the magnitude and mechanisms of global temperature variability with warming. Nature Climate Change, 7 (10). pp. 743-748. ISSN 1758-678X. https://resolver.caltech.edu/CaltechAUTHORS:20171020-082445084

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Abstract

Natural unforced variability in global mean surface air temperature (GMST) can mask or exaggerate human-caused global warming, and thus a complete understanding of this variability is highly desirable. Significant progress has been made in elucidating the magnitude and physical origins of present-day unforced GMST variability, but it has remained unclear how such variability may change as the climate warms. Here we present modelling evidence that indicates that the magnitude of low-frequency GMST variability is likely to decline in a warmer climate and that its generating mechanisms may be fundamentally altered. In particular, a warmer climate results in lower albedo at high latitudes, which yields a weaker albedo feedback on unforced GMST variability. These results imply that unforced GMST variability is dependent on the background climatological conditions, and thus climate model control simulations run under perpetual pre-industrial conditions may have only limited relevance for understanding the unforced GMST variability of the future.


Item Type:Article
Related URLs:
URLURL TypeDescription
https://doi.org/10.1038/nclimate3381DOIArticle
https://www.nature.com/nclimate/journal/v7/n10/full/nclimate3381.htmlPublisherArticle
http://rdcu.be/w4gaPublisherFree ReadCube access
ORCID:
AuthorORCID
Hill, Spencer A.0000-0001-8672-0671
Additional Information:© 2017 Macmillan Publishers Limited, part of Springer Nature. Received 13 October 2016; Accepted 03 August 2017; Published online 04 September 2017. We would like to acknowledge M. Winton and T. Knutson for internal reviews and discussion of this work. We acknowledge the World Climate Research Programme’s Working Group on Coupled Modelling, which is responsible for CMIP, and we thank the climate modelling groups for producing and making available their model output. For CMIP, the US Department of Energy’s Program for Climate Model Diagnosis and Intercomparison provides coordinating support and led development of software infrastructure in partnership with the Global Organization for Earth System Science Portals. This research was partially conducted at the NOAA Geophysical Fluid Dynamics Laboratory, Princeton, New Jersey and it was partially supported by NIH-1R21AG044294-01A1. S.A.H. was supported by a Department of Defense National Defense Science and Engineering Graduate Fellowship and a National Science Foundation Atmospheric and Geospace Sciences Postdoctoral Research Fellowship. Author Contributions: Y.M. conceived of the study. S.A.H. proposed and conducted the fixed SST model runs. P.T.B. performed the data analysis and wrote the initial draft of the manuscript. All authors contributed to interpreting results and refinement of the manuscript. The authors declare no competing financial interests.
Funders:
Funding AgencyGrant Number
NIH1R21AG044294-01A1
National Defense Science and Engineering Graduate (NDSEG) FellowshipUNSPECIFIED
NSF Postdoctoral FellowshipUNSPECIFIED
Subject Keywords:Climate and Earth system modeling; Projection and prediction
Issue or Number:10
Record Number:CaltechAUTHORS:20171020-082445084
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20171020-082445084
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:82534
Collection:CaltechAUTHORS
Deposited By: Tony Diaz
Deposited On:20 Oct 2017 17:23
Last Modified:03 Oct 2019 18:55

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