4.8 Article

Economic impacts of tipping points in the climate system

出版社

NATL ACAD SCIENCES
DOI: 10.1073/pnas.2103081118

关键词

climate tipping points; social cost of carbon; integrated assessment model; climate risk

资金

  1. Grantham Foundation for the Protection of the Environment
  2. ESRC Centre for Climate Change Economics and Policy
  3. Oxford Martin School
  4. H2020-MSCA-RISE Project GEMCLIME-2020 [681228]
  5. High Meadows Postdoctoral Fellowship at the Environmental Defense Fund

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Studies indicate that climate tipping points will increase the social cost of carbon by about 25%, with a 10% chance of doubling it. This suggests that climate tipping points will increase global economic risk and economic losses will be felt almost everywhere.
Climate scientists have long emphasized the importance of climate tipping points like thawing permafrost, ice sheet disintegration, and changes in atmospheric circulation. Yet, save for a few fragmented studies, climate economics has either ignored them or represented them in highly stylized ways. We provide unified estimates of the economic impacts of all eight climate tipping points covered in the economic literature so far using a meta-analytic integrated assessment model (IAM) with a modular structure. The model includes national-level climate damages from rising temperatures and sea levels for 180 countries, calibrated on detailed econometric evidence and simulation modeling. Collectively, climate tipping points increase the social cost of carbon (SCC) by similar to 25% in our main specification. The distribution is positively skewed, however. We estimate an similar to 10% chance of climate tipping points more than doubling the SCC. Accordingly, climate tipping points increase global economic risk. A spatial analysis shows that they increase economic losses almost everywhere. The tipping points with the largest effects are dissociation of ocean methane hydrates and thawing permafrost. Most of our numbers are probable underestimates, given that some tipping points, tipping point interactions, and impact channels have not been covered in the literature so far; however, our method of structural meta-analysis means that future modeling of climate tipping points can be integrated with relative ease, and we present a reduced-form tipping points damage function that could be incorporated in other IAMs.

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