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Comment by solinent | Hacker News Reader

Yes, it's my opinion, and I've presented it as such, but it's entirely based on his point of view. I think the opinions of non-experts are very valuable due to the effects of group-think.

The basis for my claim I could lay down, but this is not the ground for that battle.

Do you have any reason to disbelieve certain experts over others? When they are the foremost in their field, consistently? No one is denying climate change.

In any case, I don't claim its truth, just its existence. It's obviously important to any scientific process to consider alternative theories which have better predictive power, and to criticize our existing ones, however close to reality they ultimately are.

In any case, if reasonable discussion is not permitted here maybe it's not the place for me.

edit:

> That's not a good look.

Maybe I'm just in the wrong neighborhood. Okay maybe I'll stay, seems like there's a mixed response.

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> Do you have any reason to disbelieve certain experts over others?

What is important, I think, is that we shouldn't believe anyone just because they're an expert. What we believe or not should not be based on who says it, but ultimately on the data that supports it (or not).

So find the studies that (are supposed to) support a given opinion, have a look them, and have a look at how other studies in the field react to it. That last point is very important: it often reveals flaws in the study that a layman could never spot.

> In any case, I don't claim its truth, just its existence. It's obviously important to any scientific process to consider alternative theories which have better predictive power, and to criticize our existing ones, however close to reality they ultimately are.

If you go look at the climate science literature, you'll find that all different kinds of models and explanations have been proposed and studied. Those alternatives have been looked at in detail by people in the field, just like any other study. None of them have been found to better match the data.

>If you go look at the climate science literature, you'll find that all different kinds of models and explanations have been proposed and studied. Those alternatives have been looked at in detail by people in the field, just like any other study. None of them have been found to better match the data.

Because the system is chaotic and we can't predict it beyond a week. Maybe a day at best. Once you can predict hurricanes, volcanoes, and tropical storms, then let me know.

You can over-fit any data. I guess ML still has to learn this basic concept from statistics 101.

Anyways, I appreciate the discussion, thank you. I'm a bit irate this week.

You can harness chaos in space because things are really far apart. It doesn't work on Earth, or our stock market would be linear.

Because the system is chaotic and we can't predict it beyond a week. Maybe a day at best. Once you can predict hurricanes, volcanoes, and tropical storms, then let me know.

You're confusing weather and climate. We can't model the weather very well. It's hard. We can model the climate reasonably well (our models fit historical data really well), but the models turn out to be bad at predicting the future because we underestimate how much of an impact we're having (the article is a good example).

I'm not a reductionist so I don't conflate the weather and climate, but I'd consider hurricanes, volcanoes, tropical storms, and fluid flows in the ocean to be part of climate, not weather.

Hurricanes have a huge impact on animal populations, volcanoes have a huge impact on atmosphere and temperature of the core, and tropical storms are still big enough that the sum total of them is not negligible at the climate scale.

Chaotic systems sometimes don't have higher level descriptions--sufficiently chaotic systems can't be predicted at any level, and you can actually measure this. Look into the mathematical theory of chaos.

To summarize. The existing models just scratch the surface.

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