TY - JOUR
T1 - Global multi-model projections of local urban climates
AU - Zhao, Lei
AU - Oleson, Keith
AU - Bou-Zeid, Elie
AU - Krayenhoff, E. Scott
AU - Bray, Andrew
AU - Zhu, Qing
AU - Zheng, Zhonghua
AU - Chen, Chen
AU - Oppenheimer, Michael
N1 - Funding Information:
We thank the National Center for Atmospheric Research (NCAR) for supercomputing and data storage resources, including the Cheyenne supercomputer (https://doi. org/10.5065/D6RX99HX), which were provided by the Computational and Information Systems Laboratory (CISL) at NCAR. L.Z. and M.O. acknowledge the support from the High Meadows Foundation. K.O. acknowledges support by the US National Science Foundation (NSF) under grant no. AGS-1243095, and by NCAR, which is a major facility sponsored by the NSF under cooperative agreement no. 1852977. E.B.Z. acknowledges support by the Army Research Office under contract no. W911NF2010216 (program manager J. Barzyk), and the NSF under grant no. ICER 1664091 and SRN cooperative agreement no. 1444758. Q.Z. is supported by the Reducing Uncertainties in Biogeochemical Interactions through Synthesis and Computation (RUBISCO) Scientific Focus Area, Office of Biological and Environmental Research of the U.S. Department of Energy Office of Science.
Publisher Copyright:
© 2021, The Author(s), under exclusive licence to Springer Nature Limited.
PY - 2021/2
Y1 - 2021/2
N2 - Effective urban planning for climate-driven risks relies on robust climate projections specific to built landscapes. Such projections are absent because of a near-universal lack of urban representation in global-scale Earth system models. Here, we combine climate modelling and data-driven approaches to provide global multi-model projections of urban climates over the twenty-first century. The results demonstrate the inter-model robustness of specific levels of urban warming over certain regions under climate change. Under a high-emissions scenario, cities in the United States, Middle East, northern Central Asia, northeastern China and inland South America and Africa are estimated to experience substantial warming of more than 4 K—larger than regional warming—by the end of the century, with high inter-model confidence. Our findings highlight the critical need for multi-model global projections of local urban climates for climate-sensitive development and support green infrastructure intervention as an effective means of reducing urban heat stress on large scales.
AB - Effective urban planning for climate-driven risks relies on robust climate projections specific to built landscapes. Such projections are absent because of a near-universal lack of urban representation in global-scale Earth system models. Here, we combine climate modelling and data-driven approaches to provide global multi-model projections of urban climates over the twenty-first century. The results demonstrate the inter-model robustness of specific levels of urban warming over certain regions under climate change. Under a high-emissions scenario, cities in the United States, Middle East, northern Central Asia, northeastern China and inland South America and Africa are estimated to experience substantial warming of more than 4 K—larger than regional warming—by the end of the century, with high inter-model confidence. Our findings highlight the critical need for multi-model global projections of local urban climates for climate-sensitive development and support green infrastructure intervention as an effective means of reducing urban heat stress on large scales.
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U2 - 10.1038/s41558-020-00958-8
DO - 10.1038/s41558-020-00958-8
M3 - Article
AN - SCOPUS:85098773969
SN - 1758-678X
VL - 11
SP - 152
EP - 157
JO - Nature Climate Change
JF - Nature Climate Change
IS - 2
ER -