In principle, we can simply convolve the uncertainty in scenarios with the uncertainty in climate response to generate a probabilistic forecast for future climate (and Wigley and Raper did exactly this back in 2001, in a paper in Science). However, I don't think it is as simple in practice as they indicated. There are in my opinion two major difficulties with trying to generate probabilistic forecasts using the scenarios.
The first problem is that the scenarios were all explicitly and deliberately predicated on no action being specifically taken to reduce GHG emissions (although some storylines include emission reduction as a side-effect of other environmental policies). Eg, from the Technical Summary:
As required by the Terms of Reference however, none of the scenarios in the set includes any future policies that explicitly address additional climate change initiatives, although GHG emissions are directly affected by non-climate change policies designed for a wide range of other purpose.
Now, although it may sometimes seem like not much is happening yet, in fact it seems clear to me that there is at least a modest groundswell of action in roughly the right direction. The Kyoto protocol is ratified, and even the USA is taking some steps towards mitigation (especially at the local level if not federal). Ok, it is not much so far, but give it a decade or two and it seems likely to me that the IPCC scenarios will prove to be overall a pessimistic viewpoint of where we are heading. So, a "forecast" based on them is at best a forecast of where we might have been going if we took no action at all to reduce emissions, not a forecast of where we are actually heading as of today. Of course more action could be taken (some will always argue that more action is needed, whatever is actually done), but any assessment should surely be based on a realistic assessment of how much action has already been taken and what is in the pipeline. I don't know why the scenarios were designed to exclude any mitigation effects, and it makes the decision to not update them seem rather unfortunate, but perhaps someone will have a good explanation for this.
Preferences for the scenarios presented here vary among users. No judgment is offered in this report as to the preference for any of the scenarios and they are not assigned probabilities of occurrence.This is reinforced again in the summary, even more explicitly (with my bold emphasis):
Probabilities or likelihoods are not assigned to individual SRES scenarios. None of the SRES scenarios represents an estimate of a central tendency for all driving forces and emissions, such as the mean or median, and none should be interpreted as such. The statistics associated with the frequency distributions of SRES scenarios do not represent the likelihood of their occurrence. The writing team cautions against constructing a central, "best-estimate" scenario from the SRES scenarios; instead it recommends use of the SRES scenarios as they are.
In the absence of climate mitigation policies, the 90% probability interval for warming from 1990 to 2100 is 1.7C to 4.9C.There is no such thing as "the 90% probability interval for warming". There is W&R's 90% probability interval, based on their beliefs about scenarios (and their beliefs about climate sensitivity, but IMO adopting the the IPCC's "likely" range of 1.5-4.5C is relatively uncontroversial). Karl and Trenberth may also endorse this estimate if they agree with W&R's assumption. But it is not comparable to (say) the 90% confidence interval for the number of heads in 100 tosses of a fair coin.
As I've mentioned before, there is also a subjective element in the estimate of climate sensitivity - but at least this is based on a considerable amount of evidence and has been the subject of substantial debate amongst climate scientists. In contrast, the probabilistic distibution over future scenarios seems little more than a wild guess made purely on the grounds of convenience.
So, it's one thing to poke holes in research, but that leaves the question of what climate scientists should do instead. In my view, it seems unwise (and is certainly unnecessary) for them to try to make socioeconomic forecasts when economists are not prepared to do so. The obvious alternative, suggested in the SRES itself, is simply to use the different scenarios (perhaps just the marker scenarios) and present the results from each one separately. That means giving a number of probabilistic forecasts, each of which is conditional on an emissions scenario. This also makes it simple for climate scientists to make up their own scenarios which include mitigation, and demonstrate the effects that mitigation could have. This is, of course, exactly the sort of information that policy-makers should find useful. After all, future emissions are at least in part a controllable input and what we we all want to know is, to what extent we should try to control them?
Anyone who wants to make a probabilistic estimate of climate change based on their estimates of emissions and climate response is welcome to do so, of course. However, even though one can reasonably use the IPCC's estimate of climate sensitivity as the basis for one input to the calculation, there is no such consensus interpretation of the scenarios, so the assignment of probabilistic weights is entirely the researcher's own responsibility. A deliberately ignorant "uniform prior" might be defensible from a Bayesian viewpoint, but the results will be highly dependent on this assumption and I for one have little confidence in them.