[EMAIL PROTECTED] wrote:
>> On reflection I could give a slightly less glib response...we have found
>> that there is noticeable nonlinearity in at least some of our model
>> runs, but in the context of the overall uncertainty in sensitivity that
>> people often bandy about, the odd 20% here or there (say) is relatively
>> unimportant. Same goes for the sensitivity to different forcings.
>
> Thanks, I think that clarifies it quite neatly for me. Let me just
> restate it to see whether I got it right. The model runs give some non-
> linearity to different types of forcings or forcing level, but it's
> small, and on the whole clouds/water vapour should behave fairly
> "smoothly" according to the models, and we have no evidence that would
> indicate it's been large in the past. On the other hand, the
> atmosphere being a chaotic system, it cannot be entirely excluded that
> it might be significant (ie that 6 W/m2 will give 10C rather than 5C)?
> Or can it? If so, on what basis?
Chaotic is a bit of a red herring here. It's simply that we do not know
the physics in sufficient detail (and to the extent that one argues that
we do "know" classial physics, we cannot perform the calculations in
sufficient detail anyway).
>
> It's not gonna be historical precedent (we know too little about the
> forcings/temperatures going back to the last time temperature varied
> that much from present), unless we talk a small change (then we can
> look at volcanoes etc...).
>
> So, are you basically working climate sensitivity out as follows:
>
> 1. Assume linearity based on many model runs showing little deviation
> 2. Add together information from models and climatological history
> (volcanoes, ice ages) to then give a probability distribution for the
> climate sensitivity
Technically, it's not exactly an assumption of linearity, but rather a
likelihood that decays for increasing nonlinearity (at least it does for
me - there are some wacky arguments concerning probability to be found
in the literature, but let's not go there right now). But in practice if
the nonlinearity is assumed to be small, then if may be ignorable in the
calculations (given that other uncertainties are large anyway, adding
another modest one won't have much effect).
James
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