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 is sufficient to cause a GMST trend reduction with a probability of 0.40 and necessary with 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 are necessary for 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.