Paris Climate Agreement Beacon of Hope

90

able to conduct many simulations in this model framework. Figure 2.18 is similar to
Fig. 2.17, except the projection is for year 2100. The collection of histograms shown
for any particular model (i.e., either CMIP5 GCMs or EM-GC) on a specific figure
is termed the probability distribution function (PDF) for the projection of the rise in
GMST (i.e., ΔT).
The PDFs shown in Figs. 2.17 and 2.18 reveal stark differences in projections of
ΔT based on the EM-GC framework and the CMIP5 GCMs. In all cases, ΔT from
the GCMs far exceed projections using our relatively simple approach that is tightly
coupled to observed ΔT, OHC, and various natural factors that influence climate.
These differences are quantified in Table 2.1, which summarizes the cumulative
probability that a specific Paris goal can be achieved. The cumulative probabilities
shown in Table 2.1 are based on summing the height of each histogram that lies to
the left of a specific temperature, in Figs. 2.17 and 2.18.
Time series of ΔT found using the CMIP5 GCM and EM-GC approaches are
illustrated in Figs. 2.19 and 2.20, which show projections based on RCP 4.5 and

a

b

RCP 4.5

RCP 8.5

Paris Upper Limit

Paris Target

Fig. 2.18 Probability distribution functions of rise GMST, year 2100. Same as Fig. 2.17, except
all of the projections are for year 2100

2 Forecasting Global Warming