Extended Data Fig. 2: Future climate projections used in generating probabilistic, empirically-based climate change impact projections.
From: Estimating a social cost of carbon for global energy consumption
Panel (a) shows local climate distributions under the 21 climate models (outlined maps) and 12 model surrogates (dimmed maps) (‘Data assembly’ in Methods, Supplementary Sections A.2.2, A.2.3) that are weighted in climate change impact projections so that the weighted distribution of the 2080 to 2099 global mean surface temperature anomaly (ΔGMST) exhibited by the 33 total models matches the probability distribution of estimated ΔGMST responses (blue-grey line) under a high (RCP8.5) emissions scenario. For this construction, the anomaly is relative to values in 1986–2005. Maps are produced with Python programming language, using data from ref. 43 and Global Administrative Region dataset (GADM) basemap79. Panel (b) lists all 33 models and model surrogates, and their corresponding model weights for both high (RCP8.5) and moderate (RCP4.5) emissions scenarios43. These are used to capture climate model uncertainty when generating climate change impact projections under a given emissions scenario (Supplementary Section B.5).
