Local and remote mean and extreme temperature response to regional aerosol emissions reductions

Westervelt, Daniel M.; Mascioli, Nora R.; Fiore, Arlene M.; Conley, Andrew J.; Lamarque, Jean-François; Shindell, Drew T.; Faluvegi, Greg; Previdi, Michael; Correa, Gustavo; Horowitz, Larry W.

doi:https://doi.org/10.5194/acp-20-3009-2020

Articles | Volume 20, issue 5

https://doi.org/10.5194/acp-20-3009-2020

© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/acp-20-3009-2020

© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 20, issue 5

Research article

|

12 Mar 2020

Research article |

| 12 Mar 2020

Local and remote mean and extreme temperature response to regional aerosol emissions reductions

Daniel M. Westervelt, Nora R. Mascioli, Arlene M. Fiore, Andrew J. Conley, Jean-François Lamarque, Drew T. Shindell, Greg Faluvegi, Michael Previdi, Gustavo Correa, and Larry W. Horowitz

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Final revised paper (published on 12 Mar 2020)
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Interactive discussion

Status: closed

AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment

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RC1: 'Review of Westervelt et al.', Anonymous Referee #1, 27 Dec 2019
RC2: 'Review of Westervelt et al. ACP 2020', Anonymous Referee #2, 09 Jan 2020
AC1: 'Response to reviews', Daniel Westervelt, 17 Jan 2020

Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision

AR by Daniel Westervelt on behalf of the Authors (04 Feb 2020) Author's response Manuscript

ED: Publish as is (12 Feb 2020) by Pedro Jimenez-Guerrero

AR by Daniel Westervelt on behalf of the Authors (13 Feb 2020)

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Short summary

We use three Earth system models to estimate the impact of regional air pollutant emissions reductions on global and regional surface temperature. We find that removing human-caused air pollutant emissions from certain world regions (such as the USA) results in warming of up to 0.15 °C. We use our model output to calculate simple climate metrics that will allow for regional-scale climate impact estimates without the use of computationally demanding computer models.