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http://en.wikipedia.org/wiki/Chaos_theory

It would seem to me that chaos theory would suggest that it is impossible to predict with any degree of certainty any claims of future global warming specificially due to man. Too many variables, too many assumptions or simplifications/etc. in variables.

Can't claim the credit: I read a fascinating take on the modeling problem. Let's say that you have 100 parameters (I'd love to know if it a stretch to say that such complicated system as global climate can be described by 100 variables). And lets assume that we know each of the variables with 99% certainty (unbelievable certainty, but lets assume for the sake of this argument). The resulting certainty then is .99^100 = 0.3660 i.e. 36.66%.

37% is excellent if you play lottery. Is it good enough justification to spend trillions of dollars?.

BTW, if anybody can say that its wrong to argue this way, I'd like to be educated on why.

Yeppers. The IPCC puts that part in the report, er, fine print

UN IPCC WG1 Technical Summary (TS) and expert review draft TAR, Chapter 14:
"The climate system is a coupled non-linear chaotic system, and therefore the long-term prediction of future exact climate states is not possible. Rather the focus must be upon the prediction of the probability distribution of the system’s future possible states by the generation of ensembles of model solutions..."
"In sum, a strategy must recognize what is possible. In climate research and modeling, we should recognize that we are dealing with a coupled non-linear chaotic system, and therefore that the prediction of a specific future climate state is not possible. The most we can expect to achieve is the prediction of the probability distribution of the system's future possible states by the generation of ensembles of model solutions. This reduces climate change to the discernment of significant differences in the statistics of such ensembles. The generation of such model ensembles will require the dedication of greatly increased computer resources and the application of new methods of model diagnosis."