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Toward a consistent modeling framework to assess multi-sectoral climate impacts
Efforts to estimate the physical and economic impacts of future climate change face substantial challenges. To enrich the currently popular approaches to impact analysis—which involve evaluation of a damage function or multi-model comparisons based on a limited number of standardized scenarios—we pr...
Autores principales: | , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5811603/ https://www.ncbi.nlm.nih.gov/pubmed/29440736 http://dx.doi.org/10.1038/s41467-018-02984-9 |
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author | Monier, Erwan Paltsev, Sergey Sokolov, Andrei Chen, Y.-H. Henry Gao, Xiang Ejaz, Qudsia Couzo, Evan Schlosser, C. Adam Dutkiewicz, Stephanie Fant, Charles Scott, Jeffery Kicklighter, David Morris, Jennifer Jacoby, Henry Prinn, Ronald Haigh, Martin |
author_facet | Monier, Erwan Paltsev, Sergey Sokolov, Andrei Chen, Y.-H. Henry Gao, Xiang Ejaz, Qudsia Couzo, Evan Schlosser, C. Adam Dutkiewicz, Stephanie Fant, Charles Scott, Jeffery Kicklighter, David Morris, Jennifer Jacoby, Henry Prinn, Ronald Haigh, Martin |
author_sort | Monier, Erwan |
collection | PubMed |
description | Efforts to estimate the physical and economic impacts of future climate change face substantial challenges. To enrich the currently popular approaches to impact analysis—which involve evaluation of a damage function or multi-model comparisons based on a limited number of standardized scenarios—we propose integrating a geospatially resolved physical representation of impacts into a coupled human-Earth system modeling framework. Large internationally coordinated exercises cannot easily respond to new policy targets and the implementation of standard scenarios across models, institutions and research communities can yield inconsistent estimates. Here, we argue for a shift toward the use of a self-consistent integrated modeling framework to assess climate impacts, and discuss ways the integrated assessment modeling community can move in this direction. We then demonstrate the capabilities of such a modeling framework by conducting a multi-sectoral assessment of climate impacts under a range of consistent and integrated economic and climate scenarios that are responsive to new policies and business expectations. |
format | Online Article Text |
id | pubmed-5811603 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-58116032018-03-09 Toward a consistent modeling framework to assess multi-sectoral climate impacts Monier, Erwan Paltsev, Sergey Sokolov, Andrei Chen, Y.-H. Henry Gao, Xiang Ejaz, Qudsia Couzo, Evan Schlosser, C. Adam Dutkiewicz, Stephanie Fant, Charles Scott, Jeffery Kicklighter, David Morris, Jennifer Jacoby, Henry Prinn, Ronald Haigh, Martin Nat Commun Article Efforts to estimate the physical and economic impacts of future climate change face substantial challenges. To enrich the currently popular approaches to impact analysis—which involve evaluation of a damage function or multi-model comparisons based on a limited number of standardized scenarios—we propose integrating a geospatially resolved physical representation of impacts into a coupled human-Earth system modeling framework. Large internationally coordinated exercises cannot easily respond to new policy targets and the implementation of standard scenarios across models, institutions and research communities can yield inconsistent estimates. Here, we argue for a shift toward the use of a self-consistent integrated modeling framework to assess climate impacts, and discuss ways the integrated assessment modeling community can move in this direction. We then demonstrate the capabilities of such a modeling framework by conducting a multi-sectoral assessment of climate impacts under a range of consistent and integrated economic and climate scenarios that are responsive to new policies and business expectations. Nature Publishing Group UK 2018-02-13 /pmc/articles/PMC5811603/ /pubmed/29440736 http://dx.doi.org/10.1038/s41467-018-02984-9 Text en © The Author(s) 2018 Open Access 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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Monier, Erwan Paltsev, Sergey Sokolov, Andrei Chen, Y.-H. Henry Gao, Xiang Ejaz, Qudsia Couzo, Evan Schlosser, C. Adam Dutkiewicz, Stephanie Fant, Charles Scott, Jeffery Kicklighter, David Morris, Jennifer Jacoby, Henry Prinn, Ronald Haigh, Martin Toward a consistent modeling framework to assess multi-sectoral climate impacts |
title | Toward a consistent modeling framework to assess multi-sectoral climate impacts |
title_full | Toward a consistent modeling framework to assess multi-sectoral climate impacts |
title_fullStr | Toward a consistent modeling framework to assess multi-sectoral climate impacts |
title_full_unstemmed | Toward a consistent modeling framework to assess multi-sectoral climate impacts |
title_short | Toward a consistent modeling framework to assess multi-sectoral climate impacts |
title_sort | toward a consistent modeling framework to assess multi-sectoral climate impacts |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5811603/ https://www.ncbi.nlm.nih.gov/pubmed/29440736 http://dx.doi.org/10.1038/s41467-018-02984-9 |
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