The truly scary part is that many of "the science" crowd are making their policy decisions based on a MODEL of the climate, and not actual data.

Of course it's much easier to construct and run a model. You don't need to know all the inputs and outputs, you simply ignore them and continue on as though they don't matter.

Such a simplistic model only approach moves "the science" into the realm of magical thinking. It doesn't even qualify as science any more.

I use modelling extensively in my work for incredibly complex problems. As an engineer, the model has to include as many performance driving factors as possible. Understanding which of those factors matter the most takes decades of learning. Even then, the models are only an estimate. Depending on how you use them, you can explore best case performance (use optimistic inputs), worst case performance (use worst inputs), and specific cases where you can vary the inputs over parametric ranges to see where performance begins to break down.

That kind of information enables ENGINEERING based decisions, where real world designs can be based on avoiding failure zones. Later on, the real world design is compared to the model and the model is changed to reflect what actually happens, to the best extent that can be determined.

We have a couple maxims regarding modeling, to remind the old-timers and to teach the newbies:

Experience wrote..

All Models are wrong, some Models are useful.

and

Experience wrote..

A Fool with a Tool is still a Fool.

Still, there are a never ending stream of Fools, not realizing the extent of their ignorance, who believe that the Model is exactly what happens in the real world. More often than not, they will argue to their last breath that you don't understand things as well as they do.

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"War is when the Government tells you who the bad guy is. Revolution is when you decide that for yourself." - Benjamin Franklin

You can vote your way into Communism, but you have to