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Wiley Interdisciplinary Reviews Climate Change
Article . 2018 . Peer-reviewed
License: CC BY
Data sources: Crossref
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Quantifying the irreducible uncertainty in near‐term climate projections

Authors: Jochem Marotzke;

Quantifying the irreducible uncertainty in near‐term climate projections

Abstract

If the Paris agreement at the Conference of Parties 21 is implemented very effectively, greenhouse‐gas emissions might decrease after year 2020. Whether this would lead to identifiable near‐term responses in “iconic” climate quantities of wide scientific and public interest is unclear, because the climate response would be obscured by quasi‐random internal variability. I define the climate response as an increase or decrease in a linear climate trend over the period 2021–2035, compared to 2006–2020, and establish the probability of such a trend change being caused by an assumed policy shift toward emissions reductions after 2020. I quantify the irreducible uncertainty in projecting such a trend change through very large (100‐member) ensembles of the state‐of‐the‐art climate model MPI‐ESM‐LR. Trends in global‐mean surface temperature (GMST) are higher over the period 2021–2035 than over 2006–2020 in one‐third of all realizations in the mitigation scenario RCP2.6, interpreted as implementing the Paris agreement, compared to around one‐half in the no‐mitigation scenario RCP4.5. Mitigation issufficientto cause a GMST trend reduction with a probability of 0.40 andnecessarywith a probability of 0.33. Trend increases in Arctic September sea‐ice area and the Atlantic meridional overturning circulation are caused by the emissions reductions with a probability of only around 0.1. By contrast, emissions reductions arenecessaryfor a trend decrease in upper‐ocean heat content with a probability of over one‐half. Some iconic climate quantities might thus by year 2035 exhibit an identifiable response to a successful Paris agreement but sometimes with low probability, creating a substantial communication challenge.This article is categorized under:Climate Models and Modeling > Knowledge Generation with Models

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
39
Top 10%
Top 10%
Top 10%
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