Linking models of human behaviour and climate alters projected climate change

Beckage, Brian; Gross, Louis J.; Lacasse, Katherine; Carr, Eric; Metcalf, Sara S.; Winter, Jonathan M.; Howe, Peter D.; Fefferman, Nina; Franck, Travis; Zia, Asim; Kinzig, Ann; Hoffman, Forrest M.

doi:10.1038/s41558-017-0031-7

Title: Linking models of human behaviour and climate alters projected climate change

Journal Article · 01 January 2018 · Nature Climate Change

DOI: https://doi.org/10.1038/s41558-017-0031-7 · OSTI ID:1415910

^[1]; Gross, Louis J. ^[2]; Lacasse, Katherine ^[3]; Carr, Eric ^[2]; Metcalf, Sara S. ^[4]; Winter, Jonathan M. ^[5]; Howe, Peter D. ^[6]; Fefferman, Nina ^[2]; Franck, Travis ^[7]; Zia, Asim ^[1]; Kinzig, Ann ^[8];

^[9]

Univ. of Vermont, Burlington, VT (United States)
Univ. of Tennessee, Knoxville, TN (United States)
Rhode Island College, Providence, RI (United States)
The State Univ. of New York at Buffalo, Buffalo, NY (United States)
Dartmouth College, Hanover, NH (United States)
Utah State Univ., Logan, UT (United States)
Climate Interactive, Belmont, MA (United States)
Arizona State Univ., Tempe, AZ (United States)
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)

Although not considered in climate models, perceived risk stemming from extreme climate events may induce behavioural changes that alter greenhouse gas emissions. Here, we link the C-ROADS climate model to a social model of behavioural change to examine how interactions between perceived risk and emissions behaviour influence projected climate change. Our coupled climate and social model resulted in a global temperature change ranging from 3.4–6.2 °C by 2100 compared with 4.9 °C for the C-ROADS model alone, and led to behavioural uncertainty that was of a similar magnitude to physical uncertainty (2.8 °C versus 3.5 °C). Model components with the largest influence on temperature were the functional form of response to extreme events, interaction of perceived behavioural control with perceived social norms, and behaviours leading to sustained emissions reductions. Lastly, our results suggest that policies emphasizing the appropriate attribution of extreme events to climate change and infrastructural mitigation may reduce climate change the most.

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Research Organization:: Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)

Sponsoring Organization:: USDOE Office of Science (SC), Biological and Environmental Research (BER)

Grant/Contract Number:: AC05-00OR22725

OSTI ID:: 1415910

Journal Information:: Nature Climate Change, Vol. 8, Issue 1; ISSN 1758-678X

Publisher:: Nature Publishing GroupCopyright Statement

Country of Publication:: United States

Language:: English

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Cited by: 88 works

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