3.3.5 Long-term stabilization scenarios

A large number of studies on climate stabilization have been published since the TAR. Several model comparison projects contributed to the new literature, including the Energy Modelling Forum’s EMF-19 (Weyant, 2004) and EMF-21 studies (De la Chesnaye and Weyant, 2006), that focused on technology change and multi-gas studies, respectively, the IMCP (International Model Comparison Project), which focused on technological change (Edenhofer et al., 2006), and the US Climate Change Science Programme (USCCSP, 2006). The updated emission scenario database (Hanaoka et al., 2006; Nakicenovic et al., 2006) includes a total of 151 new mitigation scenarios published since the SRES.

Comparison of mitigation scenarios is more complicated now than at the time of the TAR because:

• Parts of the modelling community have expanded their analysis to include non-CO₂ gases, while others have continued to focus solely on CO₂. As discussed in the previous section, multi-gas mitigation scenarios use different targets, thus making comparison more complicated.
• Some recent studies have developed scenarios that do not stabilize radiative forcing (or temperature) – but show a peak before the end of the modelling time horizon (in most cases 2100).
• At the time of the TAR, many studies used the SRES scenarios as baselines for their mitigation analyses, providing a comparable set of assumptions. Now, there is a broader range of underlying assumptions.

This section introduces some metrics to group the CO₂-only and multi-gas scenarios so that they are reasonably comparable. In Figure 3.16 the reported CO₂ concentrations in 2100 are plotted against the 2100 total radiative forcing (relative to pre-industrial times). Figure 3.16 shows that a relationship exists between the two indicators. This can be explained by the fact that CO₂ forms by far the most important contributor to radiative forcing – and subsequently, a reduction in radiative forcing needs to coincide with a reduction in CO₂ concentration. The existing spread across the studies is caused by several factors, including differences in the abatement rate among alternative gases, differences in specific forcing values for GHGs and other radiative gases (particularly aerosols), and differences in the atmospheric chemistry and carbon cycle models that are used. Here, the relationship is used to classify the available mitigation literature into six categories that vary in the stringency of the climate targets. The most stringent group includes those scenarios that aim to stabilize radiative forcing below 3 W/m². This group also includes all CO₂-only scenarios that stabilize CO₂ concentrations below 400 ppmv. In contrast, the least stringent group of mitigation scenarios have a radiative forcing in 2100 above 6 W/m² – associated with CO₂ concentrations above 660 ppmv. By far the most studied group of scenarios are those that aim to stabilize radiative forcing at 4–5 W/m² or 485–570 ppmv CO₂ (see Table 3.5).

Figure 3.16: Relationship of total radiative forcing vis-à-vis CO₂ concentration for the year 2100 (25 multi-gas stabilization scenarios for alternative stabilization targets).

The classification of scenarios, as given in Table 3.5, permits the comparison of multi-gas and CO₂-only stabilization scenarios according to groups of scenarios with comparable level of mitigation stringency. The studies have been classified on the basis of the reported targets, using the relationship from Figure 3.16 to permit comparability of studies using different stabilization metrics. The following section uses these categories (I to VI) to analyze the underlying dynamics of stabilization scenarios as a function of the stabilization target. However, it should be noted that the classification is subject to uncertainty and should thus to be used with care.

Table 3.5: Classification of recent (post-TAR) stabilization scenarios according to different stabilization targets and alternative stabilization metrics. Groups of stabilization targets were defined using the relationship in Figure 3.16. Errata

Note: ^a Ranges correspond to the 15^th to 85^th percentile of the Post-TAR scenario distribution.

Note that the classification needs to be used with care. Each category includes a range of studies going from the upper to the lower boundary. The classification of studies was done on the basis of the reported targets (thus including modeling uncertainties). In addition, also the relationship, which was used to relate different stabilization metrics, is subject to uncertainty (see Figure 3.16).