Climate modeling isn't pop sci, it's physics. Predicting the correct outcome of complex systems is hard or impossible and depends on a lot of assumptions and interactions that you have to properly account for, this stuff gets more refined over time. The general direction of the predictions hasn't changed though so ignoring that would still be unwise.
The bad process began before we even conceived a notion of a global climate, and continues only because we're used to it. But continuing it still will change the global environment forever
I don't really see how it's unfalsifiable. If you predict a certain outcome in the future and this doesn't come true then your prediction was wrong.
The question is, are we really focusing on the right things here? Predicting trends is probably better than predicting outcomes.
As you correctly alluded to, expecting accurate predictions for complex systems is actually too much to ask for and that's why I think it's important to look at the general direction that the models point to. Are these predicted trends from the 70s different from the predicted trends now? If they aren't, what arguments do we have to reject 50 years of modelling?
Perhaps for models of the future, but for historical predictions of the current climate, prior models have been astoundingly accurate, and if anything overly conservative in their predictions.
What evidence do you have that leads you to believe that the models used now will have less predictive power than those of the past which had high predictive power?
While getting to truth may be very helpful, most models just simulate observed facts and effects, to see if it is useful and can be validated. The point is not to predict, but to see how much variance different models can display, what one might learn from it and to evolve new models from that.
What is comfortable or not shouldn't be a factor. In fact most climate scientists would search for any and all redeeming factors. It is concerning how insignificant they all seem to be. Major contrary findings would make great news, get prizes and grants.
Timelines are indeed less useful and accurate, than levels of temperature and descriptions of accumulated and latent effects. Prediction is too hard and a sidetrack from all that is established peer-reviewed science so far.
No reason to believe these models are different ( it is not about the models, it is about the people building them ).
> that is not based on what actually happens?
That is not what I said. These models are used to say things about the future, so by definition they are an assumption about what actually happens.
I will try to explain my point by a fictitious example :
Researcher A is building model for global temperature supposedly correlated with compound X. Model shows that within 100 yrs the temperature will plateua and then drop off to pre-industrial levels.
The model will be considered faulty and will be tweaked until it does feel comfortable : that is, aligns with one's assumptions.
Models are crystalizations of one's assumptions, there is no truth.
Of course you use the intuition of experts within that field when building models, that's a given. I don't see what is wrong with that, that's how all models are built.
But what is it that you're trying to say about climate models? State your own assumptions please, I don't want to keep playing this guessing game.
