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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

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.

darawk 6y ago
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".
- delecti 6y ago
  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.
  - darawk 6y ago
    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.
    - delecti 6y ago
      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".
      - darawk 6y ago
        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.

darawk 6y ago

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".

delecti 6y ago
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.
- darawk 6y ago
  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.
  - delecti 6y ago
    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".
    - darawk 6y ago
      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.