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Comment by lubesGordi | Hacker News Reader

My doubt comes from not having faith in models of complex systems. There are a lot of people who share that sentiment. If it requires a PhD and a computer model to understand some thing, it should be a given that there be skeptics.

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It may require a complicated computer model to pin down exactly what the effects will be, but it doesn't take any of that to accept the basic premises that lead to accepting climate change. We know (and have known for over 100 years) that CO2 in the atmosphere slows the escape of heat energy, which means the equilibrium temperature will go up. The specifics of 1 degree or 1.5 or 1.6 are more complicated, but it's really as simple as that. When I was in grade school, we learned that there were 300 PPM of CO2 in the atmosphere, and now they're learning that there are 400 PPM of CO2.

It may take some math to figure out how much warmer you'll get, but it's simple enough to realize that if you go outside on a comfortable sunny day, and then put on a blanket, you'll get warmer.

The problematic aspects of climate change aren't its first-order effects. The worst case scenarios involve warming by a couple of degrees Celsius - much smaller than existing variations from day to day or city to city. The only reason we're concerned is that we expect, based on climate modeling, that a worldwide shift of even this relatively small magnitude will have large second order effects.

But you're getting into "why is warming bad?", when the issue is people doubting that warming might be an outcome at all.

It isn't actually that simple, though. Adding CO2 to the atmosphere in isolation, with no reaction from the environment will indeed cause warming. But we don't live in a static model. The environment reacts to things in complex ways. It's entirely possible that adding CO2 to the environment could have caused cooling, in equilibrium (by, e.g. increasing tree density in response to the increased fuel, leading to an ultimately cooler climate). It doesn't happen to work out that way, unfortunately, but it was a possibility.

Every time I've seen someone suggest that plants could have taken up the load it seems trivial to demonstrate this is not the case.

For plants to take up the load, they would need to absorb and retain 30,000,000,000 tons of additional plant matter annually. A pine tree can absorb ~1 ton/year. If you put 100 per acre, and assume the trees are 100% sequestered, you'd need 30,000,000 acres (50,000 sq. miles) of additional pine forest, where none of the material was allowed to decay back into CO2 just to break even.

Plants don't generally sequester much of the carbon they capture in their lifetimes naturally. Mostly it's the root matter of the plant that stays sequestered. So, if you wanted the world to take this up without human intervention, you'd have to figure out how to get 30,000,000,000 tons of root matter generated each year.

I agree, but that's beside the point. The point is that the earth is a complex, dynamic suite of feedback loops, where changing one knob does not necessarily lead to the simplistic outcome that it might, if all else were held constant.

Without knowing if there were some mechanism that could balance the effect of added CO2, it would indeed be possible for such a thing to exist. Without checking, you couldn't assume it didn't exist, but coming from a place of ignorance, it's not reasonable to assume such a thing does exist. So without making unfounded assumptions, upon learning that CO2 insulates, the reasonable conclusion is that the measurable increase in CO2 (~300 to ~400 PPM) will lead to warming.

There is a vast gulf between "we should assume it would be likely to cause warming, all else equal", which is more or less reasonable, and "We have proven that it would definitely cause warming".

There's no reason to assume the complex models and naive assumption don't match though, which is the point I'm trying to argue. If the first step is "we should assume it would be likely to cause warming, all else equal", then there's no reason to jump to assuming the complex models disprove that basic assumption. They might, they do in plenty of circumstances, but it's reasonable for the working assumption to start from assuming they match. The naive assumption should convince most ignorant people (which is virtually everyone, almost nobody is doing PhD level climate research, and not many more really understand that research) to listen to the PhD scientists shouting the same thing. It's not reasonable to deny the conclusion of climate change scientists with complicated models just because you don't understand them, when the simple science agrees.

There are very good reasons to do exactly that. I don't know how often you work with complex models like this - but I do all the time. They are very often wrong for very subtle reasons. It's extremely difficult to satisfactorily prove something in a descriptive analysis, especially of a complex, dynamic system.

By default, you should basically never trust any descriptive analysis of a system like climate or the economy. Climate change specifically has received so much scrutiny by now that it's probably trustworthy. But in general you should have a very low prior on this entire category of research.

You seem to be deliberately avoiding my point. The fact that some complicated models are wrong is irrelevant. The fact that you've worked with lots of complicated wrong models is irrelevant. The rational default assumption for a lay person, when the experts say that their complicated model agrees with the simplified model which can be explained to the lay person, is to tend to accept what those experts say. It makes no sense to go from "I understand the grade school science behind climate change" to "but those experts use complicated science, so they're probably wrong".

Yes, the rational default for a lay person is to accept expert consensus. But the question at hand is what weight they should give that consensus. And that weighting should change, depending on the nature of the system being understood. We're talking about credences, not point estimates of beliefs.

Please take this question in good faith, as I am not a denier, but how do we rule out unknown earth-scale homeostasis mechanisms without a full understanding of the whole system?

If you have any links or thoughts I'd appreciate it

It's known that there were "greenhouse periods" in the distant past where substantially all the glaciers melted, so whatever homeostasis mechanisms might exist can't be strong enough to prevent that scenario.

I think most folks aren't super worried about a Venus-like runaway scenario where the planet starts boiling lead.

Instead the concern is that while the planet will reach homeostasis over the long term, in the short term it will cause mass extinctions, destroy coastal communities, disrupt food production, destabilize governments, etc.

It's like saying, "Won't a city rebuild after a major disaster?" Yes, of course. New Orleans wasn't completely eradicated by Katrina. But it was also awful. If we had it within our power to avoid a disaster, we should try to avoid it.

We can look at the geological evidence from past periods when atmospheric CO2 was higher than 280 ppm. And of course that has been done in great detail.

The evidence confirms the theory.

It sounds like your doubts come from ignorance alone. There is a difference between ignorance and skepticism. For fifty years climate models have successfully predicted the future which became the now-observed past. Later models are more accurate than previous ones. The IPCC #4 models based on data known in 2000 were right on the money in predicting the subsequent 20 years. It may be true that you don't understand these models, but that does not constitute grounds for doubting them.

https://climate.nasa.gov/news/2943/study-confirms-climate-mo...

What about, for instance, all the successful engineering that is driven by models of complex systems? We don't understand bridge dynamics at an atomic level, we have complex models that require a lot of specialized education to create, understand, and use. Same goes for microprocessor engineering. No human understands the design of a modern CPU at a transistor level, that design is also handled by computers (again guided by humans with specialized education).

We can build bridges and build microprocessors. No one has bottled up one "Earth's atmosphere" in a lab and run controlled experiments on it. It's not empirical.

People actually did do just that. Historically, high altitude balloons where used study the atmosphere and gather temperature, pressure, etc. Then it’s just a question of shining light through various atmospheric mixes to see how they respond to sunlight. Rockets and satellites then refined our understanding over time.

The basic question of global warming is a fairly simple physics problem, it’s because people care so much about absolutely tiny differences that such complex models are used. Aka Mercury vs Venus surface temperatures closely line up with simple models, but on earth people care about +/- 0.1 C and even more so in terms of local weather patterns.

We have decades of data at this point that it has been getting warmer, and that less energy has been escaping into space specifically in the spectrums that co2 traps ( from satellites), in exactly the amounts expected from the c02 delta we have measured over that time (from isotope analysis, we can tell that WE added it via burning fossil fuels)

It is as certain and clear as science ever is. The idea that it isn't is due to propaganda that is very convincing.

It is extremely far from as certain as science ever is. Randomized, controlled experiments are as certain as science ever is. This is pretty far from that.

The evidence is as good as any non-controlled experiment is going to be, perhaps. But it's pretty important that we not confuse these kinds of descriptive results with the actual certainty that comes from high powered controlled trials. It's extremely easy to make reasoning errors in descriptive data analysis, that look very convincing.

The point is that the models and their accompanying scientific descriptions provide explanatory power that is a valid source of knowledge even though it is not empirical (empiricism is a false epistemology, but that's a topic for another time). If you have a bridge design produced according to good models, and another bridge design produced without using any such models or engineering knowledge, the epistemological status of the claims "this bridge design is safe" is different between the two bridge designs. That is true even before each bridge is actually built, and if it weren't true, then there would be no reason to have laws requiring bridges to be built according to certain standards (since "we wouldn't know if it's safe until we build it").

You're right that it should be a given, given human beings' innate distrust of authority. But that doesn't mean it's not also stupid and anti-intellectual. We certainly didn't get to the moon without some PhDs and computer models.

It doesn't require a PHD, you don't have to count on models, because it has already been happening for a long time. The complex models are necessary to put tight bounds on the outcome, but that it is going to get warmer is easy to show.

Yes but should be base global policy on skepticism? Especially when the stakes are so high?

Yes. You can't run controlled experiments to study the complex system of the Earth's atmosphere. It's not empirical.

That's not what the word empirical means.

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