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6.8.1. Greenhouse Modelling versus Observation

Global-mean temperature has increased by around 0.3 to 0.6�C over the past 100 years (section 6.7.1). At the same time, greenhouse gas concentrations, and atmospheric aerosol loadings have increased substantially (sections 6.4 and 6.6). To assess whether the two are associated requires the use of model simulations of the likely climatic effects of the changing atmospheric composition, and the comparison of the results with observations. Three important detection experiments will be discussed here.

Wigley & Barnett (1990) used an energy balance climate model (incorporating upwelling and diffusion within the oceans to account for their radiative damping effect). The model was forced from 1765 to 1990 using only the changes in greenhouse gas concentrations, and the response could be varied by changing the value of the climate sensitivityThe climate sensitivity is here defined as the equilibrium global-mean temperature change for a carbon dioxide doubling (Delta T 2x). Outputs from GCMs indicate that Delta T 2x lies in the range 1.5 to 4.5 degrees Celsius.. In this way, climatic feedbacks (see section 6.9.2), not explicitly modelled, can be incorporated into the model.

The model results were qualitatively consistent with the observations on the century time scale (Figure 6.12). On shorter time scales, the model failed to reproduce the inter-decadal variability of the instrumental record. Indeed, this caveat has often been used as an argument against the greenhouse hypothesis altogether. However, Wigley & Barnett (1990) point out that such variability represents the background noise against which the greenhouse signal has to be detected. Significantly, the observational record seemed to lie at the low climate sensitivity end of the output range of that predicted by GCMs (1.5 to 4.5�C). However, the situation becomes more complex if other forcing mechanisms, in addition to the enhanced greenhouse effect, are invoked. If the net century time scale effect of non-greenhouse factors (e.g. solar variability, volcanism) involved a warming, the climate sensitivity would be less than 1�C. If their combined effect were a cooling, the sensitivity could be larger than 4�C.

One possible explanation for the decadal time scale discrepancies between the model and observed data is that some other forcing mechanism has been operating which has either offset or reinforced the general warming trend at different times. Using another energy balance model, Kelly & Wigley (1992) considered solar variability as a possible candidate. The model was run with a series of sensitivities spanning the accepted range of uncertainty in order to identify the best fit between modelled and observed temperature. Two sets of forcing histories (determined by a 1-D radiative-convective model) were considered, one involving only the effect of enhanced greenhouse gas concentrations (the IPCC 1990 forcing record), the other including also the negative radiative effect of aerosol loading and stratospheric ozone depletion (the IPCC 1992 forcing record).

Table 6.8 summarises the results of Kelly & Wigley (1992). The model explicitly calculated the best fit CO2 doubling temperature (climate sensitivity) and the amount of explained variance in the observational record by each forcing history. As well as IPCC 1990 and 1992 forcing histories, different solar variables (sunspot number, length on sunspot cycle, solar diameter and rate of change of solar diameter) were considered, and combined with the greenhouse forcing.

Table 6.8. Summary results of the Wigley/Kelly model

 

Forcing

Doubling Temp. (�C)

Explained variance (%)

Green-house

Solar

Green-house

Solar

Total

IPCC 90/92

None

1.8/3.8

46.1/49.2

 

46.1/49.2

IPCC 90/92

Number

1.2/2.9

39.7/46.1

10.7/6.4

50.4/52.5

IPCC 90/92

Length

0.9/1.9

30.4/33.8

22.6/19.8

53.0/53.6

IPCC 90/92

Diameter

1.1/2.6

37.1/43.6

16.4/10.4

53.5/54.0

IPCC 90/92

Gradient

1.8/3.6

46.1/49.0

8.9/8.0

55.0/57.0

Table 6.8 demonstrates that a considerable difference in the best-fit climate sensitivities exists between the two IPCC forcing histories. If greenhouse forcing alone is considered the CO2 doubling temperature is at the low end of the range predicted by GCMs, and is in agreement with Wigley & Barnett (1990). If the negative forcing of aerosol loading and ozone depletion is also included, the climate sensitivity is much greater. This result is intuitively correct, since the radiative effects of aerosols and ozone loss would offset the warming due to increased greenhouse gases.

When solar variability is included into the model, the explained variance of the observational record is greater than for greenhouse forcing alone. This is true for all of the solar variables considered here. The forcing combination that explains the most variance in the observational record (57%) includes the effects of greenhouse gases, aerosols and ozone depletion, and the rate of change of solar diameter. The latter, it seems, is accounting for much of the inter-decadal variability in the instrumental record.

There now seems to exist a plausible explanation for why the warming has not been regular over the past 100 years, but Kelly & Wigley (1992) point out a number of caveats. Most importantly, the explained variance varies little over a range of estimates, about the best-fit value, for the CO2 doubling temperature. Thus, it remains difficult to define a precise value for the climate sensitivity. Ultimately, knowledge of the climate sensitivity provides the key to projecting the future impact of greenhouse gas emissions (section 6.9). Whilst uncertainty remains (see section 2.8), forecasting future climates will remain an imprecise science.

In addition, other possible mechanisms of climate forcing have not been considered. These could include the effects of volcanism (section 2.6.3), ocean circulation (section 2.6.4) or even the inherent random variability of the climate system. However, as other potential mechanisms are included into the model, the uncertainty in the climate sensitivity rises. If sufficient data existed to define the natural level of climate variability prior to human interference, this estimate could be used to attach error margins to the analysis of the greenhouse signal without explicit consideration of the source of the background noise. Unfortunately, such data do not exit since the period of the instrumental record contains this greenhouse signal.

Another attempt to simulate the observational temperature record used a GCM which modelled the transientThe distinction between transient and equilibrium climate change is fully discussed in section 2.8. response to anthropogenic radiative forcing (Hadley Centre, 1995). Being more computationally complex than energy-balance models (see chapter 4), the Hadley Centre model could simulate both global-mean temperature changes and inter-regional differences. The model was run, incorporating the forcing histories of both greenhouse gases and aerosols.

For the first time, a GCM was able to replicate in broad terms the slow rise in global temperature since the middle of the last century. If greenhouse gases alone were influencing climate, one would expect global temperatures to have risen by some 0.6 to 1.3�C over the last 100 years (IPCC, 1990a). By taking into account the anthropogenic sulphate aerosols, the Hadley Centre model simulated a rise in temperature close to the observed 0.5�C.

What makes the experiment so interesting was that the GCM contained simulations of the atmosphere, oceans, ice and vegetation, and can therefore be considered to be a much better representation of the climate system than earlier GCMs, containing only the atmospheric component. Such a model significantly increased the confidence in scientists' assertion that current global warming is due to an anthropogenically enhanced greenhouse effect, albeit muted by the radiative effects of atmospheric aerosol loading. Indeed, it was in response to the Hadley Centre model, and similar ones to it more recently,

that the Intergovernmental Panel on Climate Change (IPCC, 1995) indicated that the balance of [modelling] evidence suggests a discernible human influence on the global climate does exist. Nevertheless, in view of the reservations highlighted by Kelly & Wigley (1992) concerning the uncertainty of the climate sensitivity, it remains arguable whether the cause (enhanced greenhouse forcing) and effect (global warming) have been linked unequivocally.