If the default setup of the model shows a stabilisation scenario, some people seem puzzled, saying "but you seem to project a rather low temperature increase?" or "do you think it's realistic that emissions will fall like that?". On the other hand, if the default setup shows an SRES scenario, others might say "but it doesn't work, I thought the aim was to stabilise the climate", or "why do you want emissions to increase like that?".
Essentially, some are thinking "where are we going, is it a problem, how might we deviate?", whilst others ponder "what is the best destination, and hence the course towards it?".
The former are looking forwards from the present, from cause to effect, and tend to emphasise "baseline" predictions , whereas the latter are trying to look backwards from the future, from effect to cause, trying to find a problem-solving framework.
Note that this model, and the IPCC considers both approaches, reviewing both
You may also find the model flowchart and the cause-effect page helpful. Which way do you prefer the arrows to go?
In climate science, those who work with sophisticated but slow Global Circulation Models can only make forward-looking predictions based on a small set of pre-defined scenarios, whereas those who work with simple models (such as this one) are able to use them for "inverse" (backwards) calculations or within "Integrated Assessment" frameworks, eventually intending to seek the "optimum" solution. The former might emphasise uncertainties in the models, whilst the latter try to make policy-relevant analysis now, anticipating the momentum in the system .
Both approaches pose technical problems: Scenario predictions tend to diverge wildly in the future, and so cannot be extended for long enough timescales to show the effect of slowly-responding processes such as sea-level rise. Whereas inverse calculations can define a stable future, but tend to diverge more when calculating pathways away from the present.
Imagine on a ship, the lookout high in the "crows nest" has a better view than the navigator below decks, but the latter has a chart covering greater distances, including changing currents and underwater obstacles. So they may give contradictory advice to the helmsman who, knowing that the ship is heavy to steer, has to find the best compromise!
The problem-solving approach also assumes that it is possible to make an effective science-driven global agreement limiting greenhouse gas emissions, i.e. that the UN Climate Convention will achieve it's aim as expressed in Article 2 (see mitigation). Those who project current trends might be more pessimistic about this, and prefer to emphasise developing technology to enable us to reduce emissions later if necessary, or to adapt to climate change (see different pathways).
Generally, experts tend to assume that other fields are simpler than their own. Consequently, natural scientists emphasise possible non-linear climate surprises, and suggest that we change human behaviour to avoid such risks, whereas social scientists point out how difficult that is, and might be more optimistic about adaptation or technological solutions.
In the IPCC TAR Synthesis Report, the answer to the first question regarding the application of science to the challenge posed by article 2 of the UN Climate Convention, emphasises that "Climate change decision making is essentially a sequential process under general uncertainty".
This implies that we should try to make some decisions now rather than wait for perfect knowledge, but be prepared to adapt them later as the science evolves.
Rather than either fixed stabilisation pathways or no-climate-policy "scenarios", we could investigate "strategies" incorporating deliberate climate-policy feedbacks, which are robust in response to unexpected changes, working by "fuzzy control" rather than either forward or "inverse" calculations. The structure of this model has been designed with this in mind.
This task is essentially the problem of "geocybernetics". The greek word cybernaut means helmsman, and the problem of steering ships is a useful analogy. A big ship has much momentum so we cannot change course instantly, but still need to find a strategy for responding to buffeting by wind and waves and contradictory instructions, to steer a comfortable passage towards the destination.
This process will be aided by the development of "intermediate complexity" climate system models, that are sufficiently complex to reveal non-linear surprises and regional impacts, but fast enough to be used in an Integrated Assessment problem-solving framework.
However, such models are only useful if more people understand how they work. This web model is developed as a window into these processes, to enable more people to become involved. It may also enable feedback between people, to provide a quantitative framework for global dialogue, which must accompany any decision-making process.
Regarding the distribution of future emissions, people emphasising the eventual "destination" tend to speak in terms of sharing "rights" to use the limited "resource" of the atmosphere in a sustainable way, whilst those emphasising current trends tend to speak of "burden-sharing" considering the "mitigation effort" to reduce emissions from a projected "baseline".
Regarding impacts, perhaps we should remember that for many people, especially farmers or indigenous peoples depending on sustainable ecosystems, as well as for other species of life with which we share this planet, the business-as-usual "baseline" could be considered to be no anthropogenic climate change, the "burden" to be externally imposed climate impacts, and the "effort" to be adaptation!