But somehow we are supposed to assume it doesn't cause global warming. This is an absolute bullshit assumption compared to the assumptions used in climate models. Writing a program which prints out a constant temperature for Earth over time regardless of CO2 concentration is most assuradly a GIGO agenda based program.

There is plenty of reason to doubt the accuracy of global warming predictions. Even a perfect model of past trends would still have to make assumptions on CO2 production rates in the future. This variability in model output is seldom mentioned by those siting differences in predictions as evidence for invalidity of the models. There is no good reason to assume away the problem. Claiming errors of accuracy imply total lack of validity indicates a total lack of how real world applications of science works.

Engineers make assumptions all the time because it is not cost effective to test the impact of all potential variables. The key variables are assumed based on past experience and tested if being used in a new range. Pototypes are built and tested. Often they don't work exactly as predicted but are good enough. If they don't work satisfactorily assumptions are re-evaluated. The assumption that a greenhouse gas is not going to cause global warming can be tested approximately through models or absolutely by just waiting to see if there is an impact. I think it is clear which the rational approach is. One option gives you lead time to avoid problems the other does not.

In my own chemical process work I have to make assumptions all the time to troubleshoot a problem or improve a process. Fortunately I usually get quick realtime feedback to judge the accuracy of my assumptions unlike climate modelers. It is clear they are highly involved in model testing and improvement, but it is very slow going for them with programs that take months on supercomputers!

Rejection of models because just because they are models is pure bullshit. Rejection of a particular model because you disagree with an assumption or equation in it based on real data is fine. I have yet to see evidence that anyone here has an ounce of meteorlogical expertise compared to those working in the field. I usually find the model pot shots taken here rather easy to reject based on basic science principles and common sense with only mass and energy balance related expertise yet the replies are often ignored because "they are too long winded" or handwaivingly dismissed as dogma. Neither response is remotely scientific for people claiming to having a scientific basis for rejecting global warming.

Asking for perfection in models that contain so many variables that they strain top supercomputers when there are obviously variables we still don't understand is also a cheap cop-out. There is no theory or model with anything like the detail of climate models indicating a proven greenhouse gas will not cause global warming yet somehow many here think the onus is on perfect postdiction by climate models rather than proof that a theory defying common sense has any worth. It is certain that models have not proven Global warming will be a serious issue, it is also certain that there is no good reason to believe it will not. Common sense and the preponderence of evidence suggests that GW is a potential problem just as the data on exoplanets suggests but does not yet prove Earth-like planets are rare.

Regards,
Mark