First of all, I want to add the disclaimer that I am not a climate sceptic or anything. I honestly want to understand this phenomenon. Hopefully, someone can also go into the details as I do have somewhat of a statistical background.
According to the Guardian article, "‘Word salad of nonsense’: scientists denounce Jordan Peterson’s comments on climate models", Jordan Peterson made the claim that climate models couldn't be relied on because errors compound as you forecast further into the future:
[Peterson] said: "Another problem that bedevils climate modelling, too, which is that as you stretch out the models across time, the errors increase radically. And so maybe you can predict out a week or three weeks or a month or a year, but the farther out you predict, the more your model is in error.
"And that’s a huge problem when you’re trying to model over 100 years because the errors compound just like interest."
Scientists have responded saying this understanding is wrong:
Dr Sarah Perkins-Kirkpatrick, a climate scientist at the University of New South Wales Canberra, said Peterson’s description of how climate models work was fundamentally wrong. While weather forecasts do become less accurate the further out they go, this was a different process to climate modelling. [...]
Prof Steve Sherwood, of the Climate Change Research Centre at the University of New South Wales, said Peterson was “making the ancient climate sceptic error of mixing up weather and climate”.
“Anyone who has taken an introductory course in climate or atmospheric science would spot this problem,” he said. “Errors in a weather forecast indeed accumulate such that after a couple of weeks the forecast is useless.”
But with climate, Sherwood said, the models work differently to project how the climate will respond to different factors, such as higher levels of CO2.
So why is this the case? Why don't errors accumulate?