Extended Data Fig. 6: Geographical distribution of surface trends.
From: Machine-learning-based evidence and attribution mapping of 100,000 climate impact studies

Temperature from 1951 to 2018 (left) and precipitation trends from 1951 to 2016 (right) in (a),(b) observations and (c),(d) CMIP6 10-model ensemble mean all-forcing runs. Bottom panels (e),(f) show observations categorised into attribution categories, following refs. 8,7, respectively. Observed cooling/warming or drying/wetting trends that–after accounting for internal climate variability–are inconsistent with the simulated response to natural forcings but consistent with the simulated response to both natural and anthropogenic forcings are indicated by categories -/+2. This is clearest case of changes that are at least partially attributable to anthropogenic forcing, according to the CMIP6 ensemble. Categories -/+1 have detectable observed changes, but are not assessed as attributable to anthropogenic forcing because the observed changes are significantly less than those simulated in the average all-forcing runs. Categories -/+3 have detectable changes and are assessed as at least partly attributable anthropogenic forcing, although the observed changes are inconsistent with the all-forcing runs. That is, they are in the same direction as, but are significantly stronger than, the mean of the all-forcing runs. Categories -/+4 represents cooling/warming or drying/wetting trends that are inconsistent with the simulated response to natural forcings but whose sign is opposite to that of the average simulated all-forcing response; category 0 represents trends that are not distinguishable from natural variability alone. Categories -/+4 and 0 are considered to be examples of non-detectable trends).