Multisectoral climate impact hotspots in a warming world
(2014) In Proceedings of the National Academy of Sciences of the United States of America 111(9). p.3233-3238- Abstract
The impacts of global climate change on different aspects of humanity's diverse life-support systems are complex and often difficult to predict. To facilitate policy decisions on mitigation and adaptation strategies, it is necessary to understand, quantify, and synthesize these climate-change impacts, taking into account their uncertainties. Crucial to these decisions is an understanding of how impacts in different sectors overlap, as overlapping impacts increase exposure, lead to interactions of impacts, and are likely to raise adaptation pressure. As a first step we develop herein a framework to study coinciding impacts and identify regional exposure hotspots. This framework can then be used as a starting point for regional case... (More)
The impacts of global climate change on different aspects of humanity's diverse life-support systems are complex and often difficult to predict. To facilitate policy decisions on mitigation and adaptation strategies, it is necessary to understand, quantify, and synthesize these climate-change impacts, taking into account their uncertainties. Crucial to these decisions is an understanding of how impacts in different sectors overlap, as overlapping impacts increase exposure, lead to interactions of impacts, and are likely to raise adaptation pressure. As a first step we develop herein a framework to study coinciding impacts and identify regional exposure hotspots. This framework can then be used as a starting point for regional case studies on vulnerability and multifaceted adaptation strategies. We consider impacts related to water, agriculture, ecosystems, and malaria at different levels of global warming. Multisectoral overlap starts to be seen robustly at a mean global warming of 3 °C above the 1980-2010 mean, with 11% of the world population subject to severe impacts in at least two of the four impact sectors at 4 °C. Despite these general conclusions, we find that uncertainty arising from the impact models is considerable, and larger than that from the climate models. In a low probability-high impact worst-case assessment, almost the whole inhabited world is at risk for multisectoral pressures. Hence, there is a pressing need for an increased research effort to develop a more comprehensive understanding of impacts, as well as for the development of policy measures under existing uncertainty.
(Less)
- author
- publishing date
- 2014-03-04
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- Coinciding pressures, Differential climate impacts, ISI-MIP
- in
- Proceedings of the National Academy of Sciences of the United States of America
- volume
- 111
- issue
- 9
- pages
- 6 pages
- publisher
- National Academy of Sciences
- external identifiers
-
- pmid:24344270
- scopus:84895808871
- ISSN
- 0027-8424
- DOI
- 10.1073/pnas.1222471110
- language
- English
- LU publication?
- no
- additional info
- Supporting information online at www.pnas.org/lookup/suppl/doi:10.1073/pnas.1222471110/-/DCSupplemental.
- id
- 1d393806-e7cf-42ec-a910-3e4d607c86fb
- date added to LUP
- 2020-11-19 23:22:59
- date last changed
- 2024-09-05 09:46:41
@article{1d393806-e7cf-42ec-a910-3e4d607c86fb,
abstract = {{<p>The impacts of global climate change on different aspects of humanity's diverse life-support systems are complex and often difficult to predict. To facilitate policy decisions on mitigation and adaptation strategies, it is necessary to understand, quantify, and synthesize these climate-change impacts, taking into account their uncertainties. Crucial to these decisions is an understanding of how impacts in different sectors overlap, as overlapping impacts increase exposure, lead to interactions of impacts, and are likely to raise adaptation pressure. As a first step we develop herein a framework to study coinciding impacts and identify regional exposure hotspots. This framework can then be used as a starting point for regional case studies on vulnerability and multifaceted adaptation strategies. We consider impacts related to water, agriculture, ecosystems, and malaria at different levels of global warming. Multisectoral overlap starts to be seen robustly at a mean global warming of 3 °C above the 1980-2010 mean, with 11% of the world population subject to severe impacts in at least two of the four impact sectors at 4 °C. Despite these general conclusions, we find that uncertainty arising from the impact models is considerable, and larger than that from the climate models. In a low probability-high impact worst-case assessment, almost the whole inhabited world is at risk for multisectoral pressures. Hence, there is a pressing need for an increased research effort to develop a more comprehensive understanding of impacts, as well as for the development of policy measures under existing uncertainty.</p>}},
author = {{Piontek, Franziska and Pugh, Thomas A.M. and Clark, Douglas B. and Deryng, Delphine and Elliott, Joshua and De Jesus Colón González, Felipe and Flörke, Martina and Folberth, Christian and Franssen, Wietse and Frieler, Katja and Friend, Andrew D. and Gosling, Simon N. and Hemming, Deborah and Khabarov, Nikolay and Kim, Hyungjun and Lomas, Mark R. and Masaki, Yoshimitsu and Mengel, Matthias and Morse, Andrew and Neumann, Kathleen and Nishina, Kazuya and Ostberg, Sebastian and Pavlick, Ryan and Ruane, Alex C. and Schewe, Jacob and Schmid, Erwin and Stacke, Tobias and Tang, Qiuhong and Tessler, Zachary D. and Tompkins, Adrian M. and Warszawski, Lila and Wisser, Dominik and Schellnhuber, Hans Joachim}},
issn = {{0027-8424}},
keywords = {{Coinciding pressures; Differential climate impacts; ISI-MIP}},
language = {{eng}},
month = {{03}},
number = {{9}},
pages = {{3233--3238}},
publisher = {{National Academy of Sciences}},
series = {{Proceedings of the National Academy of Sciences of the United States of America}},
title = {{Multisectoral climate impact hotspots in a warming world}},
url = {{http://dx.doi.org/10.1073/pnas.1222471110}},
doi = {{10.1073/pnas.1222471110}},
volume = {{111}},
year = {{2014}},
}