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Urban adaptation can roll back warming of emerging megapolitan regions

Open access
Georgescu, Matei, Morefield, Philip E., Bierwagen, Britta G., Weaver, Christopher P.·2014·Proceedings of the National Academy of Sciences

Abstract

Significance: Conversion to urban landforms has consequences for regional climate and the many inhabitants living within the built environment. The purpose of our investigation was to explore hydroclimatic impacts of 21st century urban expansion across the United States and examine the efficacy of commonly proposed urban adaptation strategies in context of long-term global climate change. We show that, in the absence of any adaptive urban design, urban expansion across the United States imparts warming over large regional swaths of the country that is a significant fraction of anticipated temperature increases resulting from greenhouse gas-induced warming. Adapting to urban-induced climate change is geographically dependent, and the robust analysis that we present offers insights into optimal approaches and anticipated tradeoffs associated with varying expansion pathways.

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Metadata

Authors
Georgescu, M., Morefield, P. E., Bierwagen, B. G., & Weaver, C. P.
Venue
Proceedings of the National Academy of Sciences
Published
2014-02-10
Volume
111
Issue
8
Pages
2909-2914
ISSN
  • 0027-8424 (ISSN-L)
  • 1091-6490
OpenAlex
W2099149233
Cited by
499
References
4
FWCI
39.07
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Urban adaptation can roll back warming of emerging megapolitan regions. https://app.cochat.ai/papers/10.1073/pnas.1322280111
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Georgescu, M., Morefield, P. E., Bierwagen, B. G., & Weaver, C. P. (2014). Urban adaptation can roll back warming of emerging megapolitan regions. Proceedings of the National Academy of Sciences. https://doi.org/10.1073/pnas.1322280111

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.