The Atlantic is cooling at record speed and nobody knows why

I'd expect a model that is expected to be accurate over a handful of decades would in fact be predictive on the scale of a year or a few years.

I also specifically left open the avenue that a model didn't predict this as a likely outcome but did have smaller probability outcomes that would have predicted a temperature decrease.

Its reasonable enough that the model may have found this as unlikely, but unreasonable if the model was so wrong that it wasn't even aware of this as a possible outcome in the first few years of the model. The data simply can't be useful 30 years out when it has such blind spots only a year or a few years out.

For clarity, when I mention models here I mean all recent environmental models attempting to predict global climate or specifically ocean temperatures. If we have no idea why the temperature has dropped then every model failed to provide any scenarios where that would have happened.

If you dig into what those models do, well... cover your eyes. Some frequently run off the rails and predict a climate like Venus or Pluto. They're non-deterministic and don't always do this. Obviously that's due to bugs but the bugs don't get fixed. Instead they just do lots of runs and pick the ones that don't go crazy.

"Could be" is the real key there in my opinion. We simply don't know.

And I don't mean that in any kind of climate change denial sense, those arguments fall into the same trap as anyone arguing that we definitely know how and why climate will change and why it is changing.

We don't have the data for it, and a system on the scale of the entire planet is simply too complex to be able to predict.

My big worry when it comes to climate isn't what mass extinction events could be coming, its the fear that potential creates. Fear as scale always leads to bad outcomes. Fear gives us authoritarians, bigotry, wars, and on and on.

We need to recognize that society is almost certainly drastically outstripping planetary boundaries. Once we accept that we need to move towards simple changes we can make like reducing consumption, and we need to focus heavily on embracing the uncertainty of life rather than fearing it.

[0]https://www.youtube.com/watch?v=mlhj-0iAiMQ [1]https://en.wikipedia.org/wiki/Potential_temperature

The record cover was reported in 2022: https://www.bbc.com/news/world-australia-62402891

But i agree that it got less publicity.

For example, what does every theoretical statistics textbook say about both kinds of out-of-distribution predictions? (statistics can only predict continuous functions in the ranges it has data about. And this is badly expressed. In reality there is a "minimum smoothness" the function must have if you want to be successful in predicting (ie. no spikes), and the smoothness requirement gets relaxed somewhat if you have more data, but not much, even with extreme amounts of data. Out of distribution predictions, of course, lead to disaster regardless of how much data you have, as the data is irrelevant).

I get it, "theoretical statistics" is a synonym for "nobody has ever read it, nor ever will", but it kind of is what the whole thing is based on nevertheless.

No worries, I'm sure machine learning will solve it all, of course.

Not that the IPCC report uses theoretical statistics. I would call what it uses "political" statistics. Not in the sense that they choose the outcome (perse), but in the sense that they use methods selected to maximize participation (e.g. giving absolute maximum credit). For example, how do you average 20 models, all based on different principles? When you don't know which is right? Well, it's easy, really. You take out 2-3 models you don't like (but still mention and credit them), then average the models' predictions. And that theoretical statisticians say "that's unfair! Here's a proof can get any prediction you want that way!" is met with "shut up" comments. Well, after checking if that proof wasn't wrong, of course. It wasn't.