As a software engineer who has written simulations before, I can assert that this is almost always the case with simulations. The more complex the phenomena is that you're trying to model, the more likely it is that the simulation is completely wrong because you got a single parameter slightly off.

That's why I'm skeptical of climate simulations too because they are insanely complex and they're certainly missing a lot of parameters. For example, just off the top of my head, I wonder if climate models factor in the fact that tree populations will evolve to adapt to increased CO2... I don't think they can model evolutions of tree populations because it gets into genetics. Which is a level of complexity far beyond what even the top supercomputers can simulate and even then, a lot of things would have to be simplified to the point that the model ends up having nothing to do with the real world. The butterfly effect is one of the reasons why complex simulations are not useful in predicting anything.

Simulations of complex phenomena are completely useless IMO.

You can always cherry pick one simulation out of thousands which is reliable for a few years in a row but they fall apart sooner and later so you end up using a different simulation every few years... And people keep coming up with excuses every time saying that the supercomputers were not fast enough the year before.