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A temperature binning approach for multi-sector climate impact analysis
Characterizing the future risks of climate change is a key goal of climate impacts analysis. Temperature binning provides a framework for analyzing sector-specific impacts by degree of warming as an alternative or complement to traditional scenario-based approaches in order to improve communication...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8311571/ https://www.ncbi.nlm.nih.gov/pubmed/34321705 http://dx.doi.org/10.1007/s10584-021-03048-6 |
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author | Sarofim, Marcus C. Martinich, Jeremy Neumann, James E. Willwerth, Jacqueline Kerrich, Zoe Kolian, Michael Fant, Charles Hartin, Corinne |
author_facet | Sarofim, Marcus C. Martinich, Jeremy Neumann, James E. Willwerth, Jacqueline Kerrich, Zoe Kolian, Michael Fant, Charles Hartin, Corinne |
author_sort | Sarofim, Marcus C. |
collection | PubMed |
description | Characterizing the future risks of climate change is a key goal of climate impacts analysis. Temperature binning provides a framework for analyzing sector-specific impacts by degree of warming as an alternative or complement to traditional scenario-based approaches in order to improve communication of results, comparability between studies, and flexibility to facilitate scenario analysis. In this study, we estimate damages for nine climate impact sectors within the contiguous United States (US) using downscaled climate projections from six global climate models, at integer degrees of US national warming. Each sector is analyzed based on socioeconomic conditions for both the beginning and the end of the century. The potential for adaptive measures to decrease damages is also demonstrated for select sectors; differences in damages across adaptation response scenarios within some sectors can be as much as an order of magnitude. Estimated national damages from these sectors based on a reactive adaptation assumption and 2010 socioeconomic conditions range from $600 million annually per degree of national warming for winter recreation to $8 billion annually per degree of national warming for labor impacts. Results are also estimated per degree of global temperature change and for 2090 socioeconomic conditions. |
format | Online Article Text |
id | pubmed-8311571 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
record_format | MEDLINE/PubMed |
spelling | pubmed-83115712021-12-19 A temperature binning approach for multi-sector climate impact analysis Sarofim, Marcus C. Martinich, Jeremy Neumann, James E. Willwerth, Jacqueline Kerrich, Zoe Kolian, Michael Fant, Charles Hartin, Corinne Clim Change Article Characterizing the future risks of climate change is a key goal of climate impacts analysis. Temperature binning provides a framework for analyzing sector-specific impacts by degree of warming as an alternative or complement to traditional scenario-based approaches in order to improve communication of results, comparability between studies, and flexibility to facilitate scenario analysis. In this study, we estimate damages for nine climate impact sectors within the contiguous United States (US) using downscaled climate projections from six global climate models, at integer degrees of US national warming. Each sector is analyzed based on socioeconomic conditions for both the beginning and the end of the century. The potential for adaptive measures to decrease damages is also demonstrated for select sectors; differences in damages across adaptation response scenarios within some sectors can be as much as an order of magnitude. Estimated national damages from these sectors based on a reactive adaptation assumption and 2010 socioeconomic conditions range from $600 million annually per degree of national warming for winter recreation to $8 billion annually per degree of national warming for labor impacts. Results are also estimated per degree of global temperature change and for 2090 socioeconomic conditions. 2021-03-19 /pmc/articles/PMC8311571/ /pubmed/34321705 http://dx.doi.org/10.1007/s10584-021-03048-6 Text en https://creativecommons.org/licenses/by/4.0/This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Sarofim, Marcus C. Martinich, Jeremy Neumann, James E. Willwerth, Jacqueline Kerrich, Zoe Kolian, Michael Fant, Charles Hartin, Corinne A temperature binning approach for multi-sector climate impact analysis |
title | A temperature binning approach for multi-sector climate impact analysis |
title_full | A temperature binning approach for multi-sector climate impact analysis |
title_fullStr | A temperature binning approach for multi-sector climate impact analysis |
title_full_unstemmed | A temperature binning approach for multi-sector climate impact analysis |
title_short | A temperature binning approach for multi-sector climate impact analysis |
title_sort | temperature binning approach for multi-sector climate impact analysis |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8311571/ https://www.ncbi.nlm.nih.gov/pubmed/34321705 http://dx.doi.org/10.1007/s10584-021-03048-6 |
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