The final three rows list some studies using non-uniform prior distributions, while the other studies use uniform prior distributions of ECS, except for Gregory et al. (2002a) who implicitly use a uniform prior on transient climate response (see Frame et al., 2005), and Annan et al. (2005) who select a range based on sampling
uncertain parameters in their model.
Deterministic analyses are based on best - guess estimates
for uncertain parameters, whereas probabilistic analyses explicitly consider key uncertainties of the coupled socio - natural system by describing one or more parameters in terms of probability distributions.
However, every bit of added complexity, while intended to improve some aspect of simulated climate, also introduces new sources of possible error (e.g.,
via uncertain parameters) and new interactions between model components that may, if only temporarily, degrade a model's simulation of other aspects of the climate system.
Lastly, while there are wide variations in plausible scenarios around the future of the homeownership rate, they require
many uncertain parameters, which makes it difficult to say with much confidence how the homeownership rate will evolve.
A2009 also use a large ensemble of model runs,
varying uncertain parameters, and conclude that total (fossil fuel + net land use) carbon emissions of 1000 GtC would most likely yield a peak CO2 - induced warming of 2 °C, with 90 % confidence that the peak warming would be in the range 1.3 — 3.9 °C.
These are
uncertain parameters that would have to be determined and updated based on program experience.
The nature of the tuning also matters: allowing
an uncertain parameter to vary within reasonable bounds and picking the value that gives the best result, is quite different to inserting completely artificial fluxes to correct for biases.
However, for the sake of interpreting observed climate change and predicting future change it is appropriate to consider climate sensitivity as
an uncertain parameter that may, in fact, be anywhere within that range.
A2009 also use a large ensemble of model runs, varying
uncertain parameters, and conclude that total (fossil fuel + net land use) carbon emissions of 1000 GtC would most likely yield a peak CO2 - induced warming of 2 °C, with 90 % confidence that the peak warming would be in the range 1.3 — 3.9 °C.