I am always astonished by the sheer arrogance of some researches when it comes to the sophistication of their models. The usual research in a technical field is ready to concede that his models have only a certain amount of accuracy. F.e. Finite element models of dynamic shear processes have a uncertainty of 10 % and researchers developed those with the help of industry dollars for the last 20 years. The accuracy of temperature analysis in production processes is likewise excellent if the deviation is between 10 and 15 % from the actual measured values.
And here we see climate researchers professing a magnitude of knowledge about a chaotic highly complex and non-linear system that is incredibly high. I don't say that they are flat out wrong, but they are arguing on the level of percentages and claim that uncertainty is lower than a few percent.
I saw the perfection of several models in the last few years, electrical asynchronous machines only one example. But, researchers worked on those systems and models for more than 50 years and the perfection of the models is only possible because the system is closed. In a electrical machine you don't have as many uncontrollable influences as in really chaotic systems. Yes, you can have unwanted inductances or eddy currents, but those are already predictable.
And now we are at a level, where direct torque control without much measuring is possible, because simulation models have the quality and precision necessary.
So, it is not obvious to me, how anyone can claim a high precision of his models and a long-term accuracy, if there are still several unresolved issues like cloud forming...