Table 6.15: Summary of C4MIP projections for CO2 concentrations in 2100 with and without carbon cycle temperature feedbacks for the A2 scenario (Friedlingstein et al., 2006).
CO2 conc. ppm
MAGICC A2 mean 804 743
and likely range 739–858 679–803
aresults extrapolated from 2098 end year.
b results extrapolated from 2099 end year.
0
Figure 6.12: A2 scenario likely uncertainty ranges for: (a) temperature change in 2100 and, (b) CO2 concentration, comparing IPCC AR4 temperature (IPCC, 2007a) and C4MIP CO2 (Friedlingstein et al., 2006) to MAGICC results.
148 CHAPTER 6. COMBINED CLIMATE/CARBON CYCLE PARAMETERS 6.3.4 Land–surface temperatures
In general, changes in global–mean near–surface air temperature anomalies (GSAT) are used as a primary metric of climate change. The GSAT provides a single metric that encapsulates a variety of associated changes, such as the melting of ice sheets and glaciers, impacts on precipitation and evaporation regimes, and changes to phenology. The recent upward trend in this metric has become a concern for many scientists across a broad range of disciplines as the evidence suggests that the magnitude of this change has not been seen at any time during the past 1,000 years or more (Mann et al., 2008). This increase in temperature, if sustained, will most likely lead to large-scale alterations in the environmental conditions that plants and animals, including ourselves, have evolved to live in.
However, temperature changes around the globe are not evenly distributed, with warming above the global–mean expected in some areas, such as the polar regions. MAGICC does not have the capability of modelling these regional changes (a pattern scaling routine could be used for this purpose), but it is able to report separate land and ocean surface temperature changes. Indeed, the global–mean temperature is an area average derived from the land and ocean temperatures, according to the expression:
Tglobal= Tl× fl+ To× fo
(fl+ fo) (6.1)
with the land and ocean area fractions specified within MAGICC as fl= 0.315 and fo = 1 - fl
= 0.685. The ratio of land to ocean warming has a value of 1.6, based on recent observations (Chapter 3), so that:
Tl= 1.6To (6.2)
Then:
Tglobal= To(1.6fl+ fo) (6.3)
hence:
To = 0.841Tglobal (6.4)
and:
Tl= 1.346Tglobal (6.5)
This shows that, as a reasonable approximation or ‘rule-of-thumb’, the land temperature change will be about 35% greater than the global–mean temperature change. Land–surface temperature changes are, in some ways, of more immediate importance, since we live on land, and many of the services we rely on are also land–based and affected by temperature, such as agriculture and fresh water. The land is also prone to greater heat extremes.
For a 2◦C global–mean increase above pre-industrial, the land temperature increase will be around 2.7◦C. In other words, it is not just a 2◦C warming we have to be able to adapt to, if that
6.3. REVISED PROJECTIONS 149 is the target for mitigation policy, but nearly 3◦C over land. It is not clear that this issue is fully appreciated by policy–makers or the general public.
Another important consideration is understanding the degree of risk associated with particular targets. An emission pathway may be aimed toward avoiding, as an example, 2◦C of global–mean warming above pre-industrial, but what is the chance that the target will be achieved, 90%, 50% or some other level? The posterior parameter distributions derived from the MCMH–MAGICC pro-gram allow an assessment of the risks, taking into account the range of uncertainty encompassed by these distributions, that is, allowing for the response of the combined climate–carbon cycle system as represented by MAGICC, uncertainty in aerosol forcing, and uncertainty in the obser-vations. Not included are the risk of not following the assumed emission pathway, any additional non-linearities in the Earth’s climate system, ‘tipping point’ events, and any other unforeseen pro-cesses (the ‘unknown unknowns’),2as well as the limitations of using a simple climate model and its simplified representation of complex climate system processes.
The next section looks at one approach to representing risks, and then, in Chapter 7, the topic of future temperatures and emission pathways is examined further, applying the results from this chapter to some alternative scenarios.
6.3.5 Risks of exceedance
One way of considering the uncertainty around achieving a given global–mean warming target is to express it in terms of the risk of exceedance. The posterior parameter distributions from the MCMH evaluation can by applied to a future emission scenario or pathway (scenarios and pathways are discussed in Chapter 7), in the same way as the temperature change projections were produced in the A1FI example above (Section 6.3.1), but with annual temperature results sorted so as to enable cumulative distributions to be plotted.
An example is included here to illustrate this process, using the results from the A1FI and B1 scenarios, as shown in Figure 6.13(a) and (b). In addition to the global–mean temperature changes, land temperature changes have been considered for the reasons discussed in the previous section (Section 6.3.4).
These graphs show the risks of exceeding given temperature thresholds or targets, with curves provided for 2, 3 and 4◦C. The figures can be interpreted in a number of different ways. For example, given a policy target of not exceeding 2◦C of additional global–mean warming relative to pre-industrial temperatures, for the A1FI scenario in Figure 6.13(a), the black solid line indicates a 50% chance that 2◦C will be reached by about 2042, and that it is almost certain that 2◦C will be reached by the end of this century, with a 73% probability of reaching 4◦C by 2100. A lower emission scenario, B1, Figure 6.13(b), shows the 50% probability of reaching 2◦C moves out to around 2085.
2From a statement to the press made by Donald Rumsfeld, a former United States Secretary of Defense, in February 2002.
150 CHAPTER 6. COMBINED CLIMATE/CARBON CYCLE PARAMETERS
2020 2040 2060 2080 2100 0
20 40 60 80 100
Risk of exceedence, o C wrt pre−industrial
(a)
2020 2040 2060 2080 2100 0
20 40 60 80 100
(b) 2 oC
3 oC 4 oC
Figure 6.13: Risk of exceeding temperature change targets for: (a) the SRES A1FI and (b) B1 emission scenarios, from 36,000 joint parameter sets for the 11 combined climate parameter, car-bon cycle parameter and aerosol forcing posterior distributions. Solid lines are for the global-mean, dashed lines for land temperature changes.